title: In vivo label-free observation of tumor-related blood vessels in small animals using a newly designed photoacoustic 3D imaging system

abstract:
IntroductionPhotoacoustic technology can be used for non-invasive imaging of blood vessels. In this paper, we report on our prototype photoacoustic imaging system with a newly designed ultrasound sensor and its visualization performance of microvascular in animal.

MethodsWe fabricated an experimental system for animals using a high-frequency sensor. The system has two modes: still image mode by wide scanning and moving image mode by small rotation of sensor array. Optical test target, euthanized mice and rats, and live mice were used as objects.

ResultsThe results of optical test target showed that the spatial resolution was about 2 times higher than that of our conventional prototype. The image performance in vivo was evaluated in euthanized healthy mice and rats, allowing visualization of detailed blood vessels in the liver and kidneys. In tumor-bearing mice, different results of vascular induction were shown depending on the type of tumor and the method of transplantation. By utilizing the video imaging function, we were able to observe the movement of blood vessels around the tumor.

ConclusionWe have demonstrated the feasibility of the system as a less invasive animal experimental device, as it can acquire vascular images in animals in a non-contrast and non-invasive manner.


title: Chromosome breaks in breast cancers occur near herpes tumor virus sequences

abstract:
One explanation for why breast cancer has a relentless tendency to come back after treatment is that breast cancer phenomes are fluid, so it is difficult for therapy to target new phenotypes that arise. In breast cancer, viral interactions cause chromosome breakage and fusion, producing anaphase bridges containing two centromeres. Cell division then leads to more chromosome breaks, more mutations, and new cancer phenotypes. Analyses of public data from about 2100 breast cancers implicate Epstein-Barr virus (EBV or Human Herpes Virus 4) in the cycles that break chromosomes and produce anaphase bridges. EBV generates breakage cycles with highly fragmented chromosomes (chromothripsis) as an inherent feature. These episodes continually produce new cancer driver mutations. DNA at chromothripsis boundaries in breast cancers consistently matches EBV tumor variants. Breakpoints are often near known EBV binding sites, and breast cancer shares an EBV methylation signature with other known EBV cancers. Breast cancer breakpoints on all chromosomes cluster around the same positions as in cancers definitively associated with EBV infection (nasopharyngeal cancer and Burkitts lymphoma). The status of EBV in the microbiome and the presence of anaphase bridges are phenotypic markers of breast cancer that are not explicitly targeted by chemotherapy. The breast cancer phenome continually supplies new cancer driver genes that foster breast cancer recurrence.

SummaryBreaks in breast cancer chromosomes and in fragments of anaphase bridges occur mainly near regions that resemble Epstein-Barr virus (EBV) tumor variants

Extensive breaks are an inherent outcome of anaphase bridges and the reassembly of highly fragmented chromosomes continually generates new cancer driver mutations and new cancer phenotypes.

Treatment does not explicitly target the underlying breakage and reassembly cycles so breast cancer often comes back.

The breast cancer phenome is not fixed and can continuously generate new phenotypes

Graphical Abstract

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category: cancer biology


title: Chromosome breaks in breast cancers occur near herpes tumor virus sequences and explain why cancer drugs stop working


title: Chromosome breaks in breast cancers occur near herpes tumor virus sequences and explain why the cancer comes back


title: Biological integrity enhances the qualitative effectiveness of conditional mice-oak mutualisms

abstract: Scatter-hoarding decisions by rodents are key for the long-term maintenance of scattered tree populations. Decisions are determined by seed value, competition and predation risk, so that they can be influenced by the integrity of the biological system composed by trees, rodents, ungulate competitors, and rodent predators. We manipulate and model the oak-mice interaction in a Spanish dehesa, an anthropogenic savanna system suffering chronic tree regeneration failure, and quantify the joint effect of intrinsic and extrinsic factors on acorn dispersal effectiveness. First, we conducted a large-scale cafeteria field experiment, where we modified ungulate presence and predation risk, and followed mouse scatter-hoarding decisions under contrasting levels of moonlight and acorn availability. Then, we estimated the net effects of competition and risk by means of transition probability models that simulated mouse scatter-hoarding decisions according to the environmental context. Our results show that suboptimal conditions for mice balance the interaction towards the mutualism as they force mice to forage less efficiently. Under stressful conditions (predation risks and presence of ungulates), lack of antipredatory cover around dehesa trees limited transportation of acorns, but also precluded mice activities outside tree canopies. As a result, post-dispersal predation rates were reduced and large acorns had a higher probability to survive. Our work shows that inter-specific interactions preventing efficient foraging by scatter-hoarders benefitted seed dispersal. Therefore, the maintenance of the full set of producers, consumers, dispersers and predators in ecosystems is key for promoting seed dispersal effectiveness in conditional mutualisms.

category: ecology


title: Alterations in the Antioxidant Metabolites in Cotton Leaf Curl Disease Infected and Healthy Cotton Leaves

abstract: The upland cotton (Gossypium hirsutum) belongs to the family Malvaceae and cultivated since ancient times in warmer parts of the world. Pakistan is the 4th largest cotton producing country and prominent cotton yarn exporter of the world. Cotton is the major source of natural fiber and significantly contributes to the economy of Pakistan. There are many factors (biotic and abiotic) affecting the cotton yield in Pakistan. The cotton leaf curl disease (CLCuD) is one of the biotic factors and endemic in the most cotton growing areas of the country. The antioxidant enzymes and antioxidant biochemical metabolites play important role during stress. The present study was planned to compare the antioxidant enzymes and metabolites from healthy and CLCuD infected cotton leaves. Antioxidant enzymes activities including catalase, peroxidase and peroxidase were measured through different antioxidant assays and different antioxidant metabolites were also determined. During stress condition antioxidant metabolites serve as signal for the activation of antioxidant enzymes. Present study revealed that antioxidant enzymes were significantly higher in the infected cotton leaves as compared to the healthy cotton leaves. While the amount of antioxidant metabolites like total phenolic contents (TPC) and total flavonoid contents (TFC) were higher in healthy cotton leaves as compared to the infected leaves.

category: biochemistry


title: Efficient multi-gene expression in cell-free droplet microreactors

abstract: Cell-free transcription and translation systems promise to accelerate and simplify the engineering of proteins, biological circuits and metabolic pathways. Their encapsulation on microfluidic platforms can generate millions of cell-free reactions in picoliter volume droplets. However, current methods struggle to create DNA diversity between droplets while also reaching sufficient protein expression levels. In particular, efficient multi-gene expression has remained elusive. We here demonstrate that co-encapsulation of DNA-coated beads with a defined cell-free system allows high protein expression while also supporting genetic diversity between individual droplets. We optimize DNA loading on commercially available microbeads through direct binding as well as through the sequential coupling of up to three genes via a solid-phase Golden Gate assembly or BxB1 integrase-based recombineering. Encapsulation with an off-the-shelf microfluidics device allows for single or multiple protein expression from a single DNA-coated bead per 14 pL droplet. We envision that this approach will help to scale up and parallelize the rapid prototyping of more complex biological systems.

category: bioengineering


title: VALIS: Virtual Alignment of pathoLogy Image Series

abstract: Spatial analyses can reveal important interactions between and among cells and their microenvironment. However, most existing staining methods are limited to a handful of markers per slice, thereby limiting the number of interactions that can be studied. This limitation is frequently overcome by registering multiple images to create a single composite image containing many markers. While there are several existing image registration methods for whole slide images (WSI), most have specific use cases. Here, we present the Virtual Alignment of pathoLogy Image Series (VALIS), a fully automated pipeline that opens, registers (rigid and/or non-rigid), and saves aligned slides in the ome.tiff format. VALIS has been tested with 273 immunohistochemistry (IHC) samples and 340 immunofluorescence (IF) samples, each of which contained between 2-69 images per sample. The registered WSI tend to have low error and are completed within a matter of minutes. In addition to registering slides, VALIS can also using the registration parameters to warp point data, such as cell centroids previously determined via cell segmentation and phenotyping. VALIS is written in Python and requires only few lines of code for execution. VALIS therefore provides a free, opensource, flexible, and simple pipeline for rigid and non-rigid registration of IF and/or IHC that can facilitate spatial analyses of WSI from novel and existing datasets.


title: A platform of patient-derived microtumors identifies treatment response and therapeutic vulnerabilities of ovarian cancer

abstract:
BackgroundIn light of the frequent development of therapeutic resistance in cancer treatment, there is a strong need for personalized model systems representing patient tumor heterogeneity, while enabling parallel drug testing and identification of appropriate treatment responses in individual patients. Using ovarian cancer as a prime example of a heterogeneous tumor disease with complex microenvironment and high recurrence rates, we developed a 3D preclinical ovarian cancer model comprised of patient-derived microtumors (PDM) and autologous tumor-infiltrating lymphocytes (TILs) for identification of treatment vulnerabilities and validation of anti-cancer drug efficacy using immunohistochemistry, immune cell phenotyping, functional assays and protein profiling analyses.

MethodsPDM and TILs were isolated from fresh primary ovarian cancer tissue specimen using mechanical disruption and limited enzymatic digestion and were subsequently cultured in suspension in defined media in the absence of serum. The heterogeneous cellular composition of isolated PDM as well as autologous TILs was analyzed by FFPE immunohistochemistry and multi-color flow cytometry, respectively. For in-depth protein profiling of PDM we established Reverse Phase Protein Array (RPPA) analyses of >110 total and phospho-proteins. Treatment efficacy in response to chemotherapeutics as well as immunotherapeutic compounds was assessed in PDM and PDM-TIL co-cultures using a functional viability assay in microplate format.

ResultsThe enzymatic digestion of primary ovarian cancer tissue and suspension culture in defined serum-free media allowed fast and efficient recovery of patient-derived microtumors (PDM). Immunohistochemical analyses demonstrated histopathological comparability of ovarian cancer PDM with corresponding patient tumor tissue. Reverse Phase Protein Array (RPPA)-based analyses of >110 total and phospho-proteins enabled the identification of patient-specific sensitivities to standard, platinum-based therapy and thereby the prediction of potential treatment-responders. Finally, combining PDM and autologous TILs for individual efficacy testing of immune checkpoint inhibitor treatment demonstrated the potential for patient-specific enhancement of cytotoxic TIL activity by this therapeutic approach.

Conclusion3D patient-derived ovarian cancer microtumors represent a preclinical, ex vivo tumor model that reflects intertumoral heterogeneity and represent the cellular complexity of individual patient tumors. Combining protein pathway analysis and anti-cancer drug efficacy testing of PDM enables drug mode-of-action analyses and therapeutic sensitivity prediction within a clinically relevant time frame after surgery. Follow-up studies in larger cohorts are currently under way to further evaluate the applicability of this platform to support clinical decision-making and personalizing cancer treatment.


title: A platform of patient-derived microtumors identifies individual treatment responses and therapeutic vulnerabilities in ovarian cancer.


title: A platform of patient-derived microtumors identifies therapeutic vulnerabilities in ovarian cancer.


title: The genetic diversity of Ethiopian barley genotypes in relation to their geographical origin

abstract: Ethiopia is recognized as a center of diversity for barley, and its landraces are known for the distinct genetic features compared to other barley collections. The genetic diversity of Ethiopian barley likely results from the highly diverse topography, altitude, climate conditions, soil types, and farming systems. To get detailed information on the genetic diversity a panel of 260 accessions, comprising 239 landraces and 21 barley breeding lines, obtained from the Ethiopian biodiversity institute (EBI) and the national barley improvement program, respectively were studied for their genetic diversity using the 50k iSelect single nucleotide polymorphism (SNP) array. A total of 983 highly informative SNP markers were used for structure and diversity analysis. Three genetically distinct clusters were obtained from the structure analysis comprising 80, 71, and 109 accessions, respectively. Analysis of molecular variance (AMOVA) revealed the presence of higher genetic variation (89%) within the clusters than between the clusters (11%), with moderate genetic differentiation (PhiPT=0.11) and adequate gene flow (Nm=2.02). The Mantel test revealed that the genetic distance between accessions is poorly associated with their geographical distance. Despite the observed weak correlation between geographic distance and genetic differentiation, for some regions like Gonder, Jimma, Gamo-Gofa, Shewa, and Welo, more than 50% of the landraces derived from these regions are assigned to one of the three clusters.

category: genetics


title: Maf1, a repressor of RNA polymerase III-dependent transcription, regulates bone mass

abstract: Maf1, a key repressor of RNA polymerase III-mediated transcription, has been shown to promote mesoderm formation in vitro. Here, we show, for the first time, that Maf1 plays a critical role in the regulation of osteoblast differentiation and bone mass. A high bone mass phenotype was noted in mice with global deletion of Maf1 (Maf1-/- mice), as well as paradoxically, in mice that overexpressed MAF1 in cells of the osteoblast lineage (Prx1-Cre;LSL-Maf1 mice). Osteoblasts isolated from Maf1-/- mice showed reduced osteoblastogenesis ex vivo. Prx1-Cre;LSL-MAF1 mice showed enhanced osteoblastogenesis concordant with their high bone mass phenotype. Thus, the high bone mass phenotype in Maf1-/- mice is likely due to the confounding effects of the global absence of Maf1 in Maf1-/- mice. Expectedly, MAF1 overexpression promoted osteoblast differentiation and shRNA-mediated Maf1 downregulation inhibited differentiation of ST2 cells, overall indicating Maf1 enhances osteoblast formation. We also found that, in contrast to MAF1 overexpression, other perturbations that repress RNA pol III transcription, including Brf1 knockdown and the chemical inhibition of RNA pol III by ML-60218, inhibited osteoblast differentiation. All perturbations that decrease RNA pol III transcription, however, enhanced adipogenesis in ST2 cell cultures. RNA-seq was used to determine the basis for these opposing actions on osteoblast differentiation. The modalities used to alter RNA pol III transcription resulted in distinct changes gene expression, indicating that this transcription process is highly sensitive to perturbations and triggers diverse gene expression programs and phenotypic outcomes. Specifically, Maf1 induced genes in ST2 cells known to promote osteoblast differentiation. Furthermore, genes that are induced during osteoblast differentiation displayed codon bias. Together, these results reveal a novel role for Maf1 and RNA pol III-mediated transcription in osteoblast fate determination and differentiation and bone mass regulation.

category: cell biology


title: Heritability of hippocampal functional and microstructural organisation

abstract: The hippocampus is a uniquely infolded allocortical structure in the medial temporal lobe that consists of the microstructurally and functionally distinct subregions: subiculum, cornu ammonis, and dentate gyrus. The hippocampus is a remarkably plastic region that is implicated in learning and memory. At the same time it has been shown that hippocampal subregion volumes are heritable, and that genetic expression varies along a posterior to anterior axis. Here, we studied how a heritable, stable, hippocampal organisation may support its flexible function in healthy adults. Leveraging the twin set-up of the Human Connectome Project with multimodal neuroimaging, we observed that the functional connectivity between hippocampus and cortex was heritable and that microstructure of the hippocampus genetically correlated with cortical microstructure. Moreover, both functional and microstructural organisation could be consistently captured by anterior-to-posterior and medial-to-lateral axes across individuals. However, heritability of functional, relative to microstructural, organisation was found reduced, suggesting individual variation in functional organisation of subfields is under low genetic control. Last, we demonstrate that structure and function couple along its genetic axes, suggesting an interplay of stability and plasticity within the hippocampus. Our study provides new insights on the heritability of the hippocampal formation and illustrates how genetic axes may scaffold hippocampal structure and function.

category: neuroscience


title: 2-Guanidino-quinazoline promotes the readthrough of nonsense mutations underlying human genetic diseases

abstract: Premature termination codons (PTCs) account for 10% to 20% of genetic diseases in humans. The gene inactivation resulting from PTC can be counteracted by the use of drugs stimulating PTC readthrough, thereby restoring production of the full-length protein. However, a greater chemical variety of readthrough inducers is required to broaden the medical applications of this therapeutic strategy. In this study, we developed a new reporter cell line and performed high-throughput screening (HTS) to identify potential new readthrough inducers. After three successive assays, we isolated 2-guanidino-quinazoline (TLN468). We assessed the clinical potential of this drug as a potent readthrough inducer on the 40 PTCs most frequently responsible for Duchenne muscular dystrophy. We found that TLN468 was more efficient than gentamicin, and acted on a broader range of sequences, without inducing the readthrough of natural stop codons.

category: molecular biology


title: Insecticide susceptibility of Aedes (Stegomyia) aegypti (Linnaeus, 1762) and Aedes (Stegomyia) albopictus (Skuse, 1894) in Kinshasa, Democratic Republic of the Congo

abstract: Aedes aegypti and Aedes albopictus are arbovirus vectors of public health concern. Although the Democratic Republic of the Congo (DRC) faces a long-standing risk of Aedes-borne viruses, data on insecticide resistance of Aedes populations are absent. To address this gap, we investigated insecticide susceptibility of Ae. aegypti and Ae. albopictus in areas with a high risk of arbovirus transmission. We also investigated the frequency of knock-down resistance (kdr) mutations in Ae. aegypti. Immature stages of Ae. aegypti and Ae. albopictus were collected from two sites in Kinshasa (Lingwala and Cite Verte) between April and July 2017 and reared to the adult stage. Wild-caught adult Ae. aegypti were collected in 2016 in another site (Ngaliema). Female Ae. aegypti (from Lingwala) and Ae. albopictus (from Cite Verte) were used in WHO tube insecticide susceptibility tests. The F1534C, V1016I and V410L kdr mutations were genotyped in Ae. aegypti from Lingwala and Ngaliema. We observed Ae. aegypti to be susceptible to bendiocarb, propoxur and malathion, suspected resistant to permethrin, and resistant to deltamethrin and DDT. Aedes albopictus was susceptible to bendiocarb, propoxur, malathion and permethrin, suspected resistant to deltamethrin and resistant to DDT. While F1534C and V1016I were not detected, a few Ae. aegypti from Lingwala were heterozygous for the mutation V410L. This study reports for the first time the insecticide resistance status of Aedes spp. and the detection of the kdr mutation V410L in Ae. aegypti in DRC. Given the resistance profile, carbamates and potentially malathion are recommended insecticide options against Ae. aegypti in Kinshasa. It will be important to develop Aedes control strategies based on the resistance patterns of Aedes in Kinshasa.


title: Landscape, complexity and regulation of a filamentous fungal transcriptome

abstract: Alternative splicing (AS) and alternative polyadenylation (APA) of pre-mRNAs contribute greatly to transcriptome complexity and gene expression regulation in higher eukaryotes. Their biological impact in filamentous fungi, however, has been poorly studied. Here we combine PacBio Isoform Sequencing and strand-specific RNA-Seq of multiple tissues together with mutant characterization to reveal the landscape, complexity and regulation of AS and APA in the filamentous plant pathogenic fungus Fusarium graminearum. We updated the reference genome and generated a comprehensive annotation comprising 51,617 transcript isoforms from 17,189 genes. Majority of the transcripts represent novel isoforms, including 2,998 undiscovered protein-coding genes. In total, 42.7% of multi-exonic genes and 64.8% of genes have AS and APA isoforms, respectively, suggesting AS and APA increase previously unrecognized transcriptome complexity in fungi. Nonsense-mediated mRNA decay factor FgUPF1 may not degrade AS transcripts with premature-stop codons but regulate ribosome biogenesis. Distal polyadenylation sites have a strong signal but proximal polyadenylation isoforms are high expressed. The core 3-end processing factors FgRNA15, FgHRP1, and FgFIP1 play important roles in promoting proximal polyadenylation site usage and also intron splicing. Genome-wide increase in the abundance of transcripts with retained introns and long 3-UTRs and downregulation of the spliceosomal and 3-end processing factors are found in older tissues and quiescent conidia, indicating that intron retention and 3-UTR lengthening may be a transcriptional signature of aging and dormancy in fungi. Overall, our study generates a comprehensive full-length transcript annotation for F. graminearum and provides new insights into the complexity and regulation of transcriptome in filamentous fungi.

category: genomics


title: A single cell atlas of human and mouse white adipose tissue

abstract: White adipose tissue (WAT), once regarded as morphologically and functionally bland, is now recognized to be dynamic, plastic, heterogenous, and involved in a wide array of biological processes including energy homeostasis, glucose and lipid handling, blood pressure control, and host defense1. High fat feeding and other metabolic stressors cause dramatic changes in adipose morphology, physiology, and cellular composition1, and alterations in adiposity are associated with insulin resistance, dyslipidemia, and type 2 diabetes (T2D)2. Here, we provide detailed cellular atlases of human and murine subcutaneous and visceral white fat at single cell resolution across a range of body weight. We identify subpopulations of adipocytes, adipose stem and progenitor cells (ASPCs), vascular, and immune cells and demonstrate commonalities and differences across species and dietary conditions. We link specific cell types to increased risk of metabolic disease, and we provide an initial blueprint for a comprehensive set of interactions between individual cell types in the adipose niche in leanness and obesity. These data comprise an extensive resource for the exploration of genes, traits, and cell types in the function of WAT across species, depots, and nutritional conditions.

category: physiology


title: OptiFit: an improved method for fitting amplicon sequences to existing OTUs

abstract:
Assigning amplicon sequences to operational taxonomic units (OTUs) is often an important step in characterizing the composition of microbial communities across large datasets. OptiClust, a de novo OTU clustering method, has been shown to produce higher quality OTU assignments than other methods and at comparable or faster speeds. A notable difference between de novo clustering and database-dependent reference clustering methods is that OTU assignments from de novo methods may change when new sequences are added to a dataset. However, in some cases one may wish to incorporate new samples into a previously clustered dataset without performing clustering again on all sequences, such as when comparing across datasets or deploying machine learning models where OTUs are features. Existing reference-based clustering methods produce consistent OTUs, but they only consider the similarity of each query sequence to a single reference sequence in an OTU, thus resulting in OTU assignments that are significantly worse than those generated by de novo methods. To provide an efficient and robust method to fit amplicon sequence data to existing OTUs, we developed the OptiFit algorithm. Inspired by OptiClust, OptiFit considers the similarity of all pairs of reference and query sequences in an OTU to produce OTUs of the best possible quality. We tested OptiFit using four microbiome datasets with two different strategies: by clustering to an external reference database or by splitting the dataset into a reference and query set and clustering the query sequences to the reference set after clustering it using OptiClust. The result is an improved implementation of closed and open-reference clustering. OptiFit produces OTUs of similar quality as OptiClust and at faster speeds when using the split dataset strategy, although the OTU quality and processing speed depends on the database chosen when using the external database strategy. OptiFit provides a suitable option for users who require consistent OTU assignments at the same quality afforded by de novo clustering methods.

ImportanceAdvancements in DNA sequencing technology have allowed researchers to affordably generate millions of sequence reads from microorganisms in diverse environments. Efficient and robust software tools are needed to assign microbial sequences into taxonomic groups for characterization and comparison of communities. The OptiClust algorithm produces high quality groups by comparing sequences to each other, but the assignments can change when new sequences are added to a dataset, making it difficult to compare different studies. Other approaches assign sequences to groups by comparing them to sequences in a reference database to produce consistent assignments, but the quality of the groups produced is reduced compared to OptiClust. We developed OptiFit, a new reference-based algorithm that produces consistent yet high quality assignments like OptiClust. OptiFit allows researchers to compare microbial communities across different studies or add new data to existing studies without sacrificing the quality of the group assignments.

category: microbiology


title: Lysosome-targeted lipid probes reveal sterol transporters NPC1 and LIMP2 as sphingosine transporters

abstract: Lysosomes are central catabolic organelles involved in lipid homeostasis and their dysfunction is associated with pathologies ranging from lysosomal storage disorders to common neurodegenerative diseases. The mechanism of lipid efflux from lysosomes is well understood for cholesterol, while the export of other lipids, particularly sphingosine, is less well studied. To overcome this knowledge gap, we have developed functionalized sphingosine and cholesterol probes that allow us to follow their metabolism, protein interactions as well as their subcellular localization. These probes feature a modified cage group for lysosomal targeting and controlled release of the active lipids with high temporal precision. An additional photo-crosslinkable group allowed for the discovery of lysosomal interactors for both sphingosine and cholesterol. In this way, we found that two lysosomal cholesterol transporters, NPC1 and LIMP-2/SCARB2, also directly bind to sphingosine. In addition, we showed that absence of either protein leads to lysosomal sphingosine accumulation which suggests a sphingosine transport role of both proteins. Furthermore, artificial elevation of lysosomal sphingosine levels impaired cholesterol efflux, consistent with sphingosine and cholesterol sharing a common export mechanism.


title: Deamidated TPI is an efficacious target for cell-selective therapy in triple-negative breast cancer

abstract: Human TPI (HsTPI) is a central and essential glycolytic enzyme for energy supply and is overexpressed in cancer cells. Here, we investigated HsTPI as a potential target for inducing cell death in triple-hormone receptor-negative breast cancer, which is highly dependent on glycolysis, and therapies for its treatment are limited. We found endogenous accumulation of deamidated HsTPI in human breast cancer cells, which might be caused by the lower activity of the HsTPI-degrading caspase-1 in breast cancer cells. In silico and in vitro analyses of deamidated HsTPI demonstrated the efficacy of thiol-reactive drugs in blocking enzyme activity. The cancer cells were selectively programmed to undergo apoptosis with thiol-reactive drugs by inducing the production of methylglyoxal (MGO) and advanced glycation-end products (AGEs). In vivo in mice, the thiol-reactive drug effectively inhibited the growth of human tumors by targeting HsTPI as underlying mechanism. Our findings demonstrate deamidated HsTPI as a novel target to develop therapeutic strategies for treating cancers and other pathologies in which this post-translationally modified protein accumulates.


title: Once-daily feeding is associated with better cognitive function and health in companion dogs: Results from the Dog Aging Project

abstract: A variety of diets have been studied for possible anti-aging effects. In particular, studies of intermittent fasting and time-restricted feeding in laboratory rodents have found evidence of beneficial health outcomes. Companion dogs represent a unique opportunity to study diet in a large mammal that shares human environments. The Dog Aging Project has been collecting data on thousands of companion dogs of all different ages, sizes, and breeds since 2019. We leveraged this diverse cross-sectional dataset to investigate associations between feeding frequency and cognitive function (n = 10,474) as well as nine broad categories of health conditions (n = 24,238). Controlling for sex, age, breed, and other potential confounders, we found that dogs fed once daily rather than more frequently had lower mean scores on a cognitive dysfunction scale, and lower odds of having gastrointestinal, dental, orthopedic, kidney/urinary, and liver/pancreas disorders. Therefore, we find that once-daily feeding is associated with better health in multiple domains. Future research with longitudinal data can provide stronger evidence for a possible causal effect of feeding frequency on health in companion dogs.

category: animal behavior and cognition


title: Once-daily feeding is associated with better health in companion dogs: Results from the Dog Aging Project


title: REDigest: a Python GUI for In-Silico Restriction Digestion Analysis of Genes or Complete Genome Sequences

abstract: Restriction fragment length polymorphism (RFLP) is a technology for the molecular characterization of DNA and widely used genome mapping, medical genetics, molecular microbiology and forensics etc. Terminal restriction fragment length polymorphism (T-RFLP), a variant of RFLP is extensively used in environmental microbiology for the microbial community profiling based on the restriction digestion profile of marker gene (16S rRNA, FTHFS etc.) amplicons. At present, there is a lack of a tool which can perform in-silico restriction digestion of a large number of sequences at a time, in an interactive way and as an output produce sequences of the restriction fragments and visualization plot. I have developed a graphical user interface based software "REDigest" for the in-silico restriction digestion analysis for gene or genome sequences. The REDigest software program with a graphical user interface is freely available at https://github.com/abhijeetsingh1704/REDigest.

category: bioinformatics


title: Cortical and autonomic responses during staged Taoist meditation: two distinct meditation strategies.

abstract: Meditation is a consciousness state associated with specific physiological and neural correlates. Numerous investigations of these correlates reported controversial results which prevented a consistent depiction of the underlying neurophysiological processes. Here we investigated the dynamics of multiple neurophysiological indicators during a staged meditation session. We measured the physiological changes at rest and during the guided Taoist meditation in experienced meditators and naive subjects. We recorded EEG, respiration, galvanic skin response, and photoplethysmography. All subjects followed the same instructions split into 16 stages. In the experienced meditators group we identified two subgroups with different physiological markers dynamics. One subgroup showed several signs of general relaxation evident from the changes in heart rate variability, respiratory rate, and EEG rhythmic activity. The other subgroup exhibited mind concentration patterns primarily noticeable in the EEG recordings while no autonomic responses occurred. The duration and type of previous meditation experience or any baseline indicators we measured did not explain the segregation of the meditators into these two groups. These results suggest that two distinct meditation strategies could be used by experienced meditators, which partly explains the inconsistent results reported in the earlier studies evaluating meditation effects. Our findings are also relevant to the development of the high-end biofeedback systems.


title: Measuring metabolic rate in single flies during sleep and waking states

abstract: Drosophila melanogaster is a leading genetic model for studying the neural regulation of sleep. Sleep is associated with changes in behavior and physiological state that are largely conserved across species. The investigation of sleep in flies has predominantly focused on behavioral readouts of sleep because physiological measurements, including changes in brain activity and metabolic rate are less accessible. We have previously used stop-flow indirect calorimetry to measure whole body metabolic rate in single flies and have shown that in flies, like mammals, metabolic rate is reduced during sleep. Here, we describe a modified version of this system that allows for efficient and highly sensitive acquisition of CO2 output from single flies. We also describe a modification that allows for simultaneous acquisition of CO2 and O2 levels, providing a respiratory quotient that quantifies how metabolic stores are utilized. Finally, we show that sleep-dependent changes in metabolic rate are diminished in aging flies, supporting the notion that sleep quality is reduced as flies age. Taken together, the use of indirect calorimetry provides a physiological measure of sleep with broad applications to genetic studies in flies.


title: Sensitivity optimization of a rhodopsin-based fluorescent voltage indicator

abstract: The ability to optically image cellular transmembrane voltage at millisecond-timescale resolution can offer unprecedented insight into the function of living brains in behaving animals. The chemigenetic voltage indicator Voltron is bright and photostable, making it a favorable choice for long in vivo imaging of neuronal populations at cellular resolution. Improving the voltage sensitivity of Voltron would allow better detection of spiking and subthreshold voltage signals. We performed site saturation mutagenesis at 40 positions in Voltron and screened for increased {Delta}F/F0 in response to action potentials (APs) in neurons. Using a fully automated patch-clamp system, we discovered a Voltron variant (Voltron.A122D) that increased the sensitivity to a single AP by 65% compared to Voltron. This variant (named Voltron2) also exhibited approximately 3-fold higher sensitivity in response to sub-threshold membrane potential changes. Voltron2 retained the sub-millisecond kinetics and photostability of its predecessor, with lower baseline fluorescence. Introducing the same A122D substitution to other Ace2 opsin-based voltage sensors similarly increased their sensitivity. We show that Voltron2 enables improved sensitivity voltage imaging in mice, zebrafish and fruit flies. Overall, we have discovered a generalizable mutation that significantly increases the sensitivity of Ace2 rhodopsin-based sensors, improving their voltage reporting capability.


title: A novel machine learning-based approach for the detection and analysis of spontaneous synaptic currents

abstract: Spontaneous synaptic activity is a hallmark of neural networks. A thorough description of these synaptic signals is essential for understanding neurotransmitter release and the generation of a postsynaptic response. However, the complexity of synaptic current trajectories has either precluded an in-depth analysis or it has forced human observers to resort to manual or semi-automated approaches based on subjective amplitude and area threshold settings. Both procedures are time-consuming, error-prone and likely affected by human bias. Here, we present three complimentary methods for a fully automated analysis of spontaneous excitatory postsynaptic currents measured in major cell types of the mouse retina and in a primary culture of mouse auditory cortex. Two approaches rely on classical threshold methods, while the third represents a novel machine learning-based algorithm. Comparison with frequently used existing methods demonstrates the suitability of our algorithms for an unbiased and efficient analysis of synaptic signals in the central nervous system.


title: B cell clonal expansion is correlated with antigen-specificity in young but not old mice

abstract: Aging of the humoral immune response has been shown to affect its critical role in defending the host from a variety of pathogens. Technical limitations have nevertheless made it challenging to investigate the relationship between genotype and phenotype of antibody repertoires in the context of aging. We therefore performed single-cell sequencing of over 95,000 B cells to simultaneously investigate B cell receptor (BCR) repertoires and gene expression profiles in the bone marrow and spleens of young and old mice following immunizations with a protein antigen. We discovered the presence of clonally expanded B cells in both young and old mice, which had distinct transcriptional phenotypes and exhibited age-associated gene signatures relating to plasma cell differentiation and protein folding and stabilization genes. Recombinant expression of 227 monoclonal antibodies revealed that clonally expanded B cells were frequently antigen-specific in young mice but not in old mice. Furthermore, we detected clonal convergence across different mice which was correlated with antigen-specificity. Although isotype- and expansion-specific transcriptional phenotypes could be detected, there was little correlation with antigen-specificity and transcriptional signatures. Together, our work provides an age-resolved single-cell repertoire resource that further relates antibody specificity, repertoire features, and whole transcriptomes.

category: immunology


title: Measuring the invisible - The sequences causal of genome size differences in eyebrights (Euphrasia) revealed by k-mers

abstract:
Genome size variation within plant (and other) taxa may be due to presence/absence variation in low-copy sequences or copy number variation in genomic repeats of various frequency classes. However, identifying the sequences underpinning genome size variation has been challenging because genome assemblies commonly contain collapsed representations of repetitive sequences and because genome skimming studies miss low-copy number sequences.

Here, we take a novel approach based on k-mers, short sub-sequences of equal length k, generated from whole genome sequencing data of diploid eyebrights (Euphrasia), a group of plants which have considerable genome size variation within a ploidy level. We compare k-mer inventories within and between closely related species, and quantify the contribution of different copy number classes to genome size differences. We further assign high-copy number k-mers to specific repeat types as retrieved from the RepeatExplorer2 pipeline.

We find complex patterns of k-mer differences between samples. While all copy number classes contributed to genome size variation, the largest contribution came from repeats with 1000-10,000 genomic copies including the 45S rDNA satellite DNA and, unexpectedly, a repeat associated with an Angela transposable element. We also find size differences in the low-copy number class, likely indicating differences in gene space between our samples.

In this study, we demonstrate that it is possible to pinpoint the sequences causing genome size variation within species without use of a reference genome. Such sequences can serve as targets for future cytogenetic studies. We also show that studies of genome size variation should go beyond repeats and consider the whole genome. To allow future work with other taxonomic groups, we share our analysis pipeline, which is straightforward to run, relying largely on standard GNU command line tools.

category: evolutionary biology


title: Estimating the rates of crossover and gene conversion from individual genomes

abstract: Recombination can occur either as a result of crossover or gene conversion events. Population genetic methods for inferring the rate of recombination from patterns of linkage disequilibrium generally assume a simple model of recombination that only involves crossover events and ignore gene conversion. However, distinguishing the two processes is not only necessary for a complete description of recombination, but also essential for understanding the evolutionary consequences of inversions and other genomic partitions in which crossover (but not gene conversion) is reduced. We present heRho, a simple composite likelihood scheme for co-estimating the rate of crossover and gene conversion from individual diploid genomes. The method is based on analytic results for the distance-dependent probability of heterozygous and homozygous states at two loci. We apply heRho to simulations and data from the house mouse Mus musculus castaneus, a well studied model. Our analyses show i) that the rates of crossover and gene conversion can be accurately co-estimated at the level of individual chromosomes and ii) that previous estimates of the population scaled rate of recombination [Formula] under a pure crossover model are likely biased.


title: Quantitative isotope-labeled crosslinker proteomics reveals developmental variation in protein interactions and posttranslational modifications in Diaphorina citri, the citrus greening insect vector

abstract: Acquisition of the citrus greening bacterial pathogen,  Candidatus Liberibacter asiaticus (CLas) by Asian citrus psyllid (Diaphorina citri) nymphs is required efficient tree-to-tree transmission during the adult stage. Quantitative isotope-labeled protein interaction reporter (PIR) cross-linkers were used in parallel with protein quantification using spectral counting to quantify protein interactions within microbe-enriched cellular fractions of nymph and adult D. citri. Over 100 unique crosslinks were found between five insect histone proteins, and over 30% of these were more abundant in nymph compared to adult insects. Strikingly, some cross-links detected in D. citri proteins are conserved in cross-linking studies on human cells, suggesting these protein interaction topologies were present in the common ancestor ([~]750MYA) or are subject to convergent evolution. Analysis of posttranslational modifications of crosslinked histones revealed the presence of acetylated and methylated lysine residues, which may impact psyllid chromatin structure and gene expression. Histone H3 peptides acetylated in the N terminal tail region were found to be more abundant in nymph compared to adult insects in two orthogonal proteomics methods. The insect life stage-specific histone posttranslational modifications and protein interactions represent physical evidence that metamorphosis is associated with changes in chromatin structure that regulate genome-wide transcriptional reprogramming.

category: systems biology


title: Accurate inference of stochastic gene expression from nascent transcript heterogeneity

abstract: Transcriptional rates are often estimated by fitting the distribution of mature mRNA numbers measured using smFISH (single molecule fluorescence in situ hybridization) with the distribution predicted by the telegraph model of gene expression, which defines two promoter states of activity and inactivity. However, fluctuations in mature mRNA numbers are strongly affected by processes downstream of transcription. In addition, the telegraph model assumes one gene copy, but in experiments cells may have two gene copies as cells replicate their genome during the cell cycle. It is thus unclear how accurately the inferred parameters reflect transcription. To address these issues, here we measure both mature and nascent mRNA distributions of GAL10 in yeast cells using smFISH and classify each cell according to its cell cycle stage. We infer transcriptional parameters from mature and nascent mRNA distributions, with and without accounting for cell cycle stage and compare the results to live-cell transcription measurements of the same gene. We conclude that: (i) not accounting for cell cycle dynamics in nascent mRNA data overestimates the magnitude of promoter switching rates and the initiation rate, and underestimates the fraction of time spent in the active state and the burst size. (ii) use of mature mRNA data, instead of nascent data, significantly increases the errors in parameter estimation and can mistakenly classify a gene as non-bursting. Furthermore, we show how to correctly adjust for measurement noise in sm-FISH at low nascent transcript numbers. Simulations with parameters estimated from nascent smFISH data corrected for cell cycle phases and measurement noise leads to autocorrelation functions that agree with those obtained from live-cell imaging. Therefore, our novel data curation method yields a quantitatively accurate picture of gene expression.


title: Heterogeneous CaMKII-dependent synaptic compensations in CA1 pyramidal neurons from acute slices with dissected CA3

abstract: Prolonged changes in neural activity trigger homeostatic synaptic plasticity (HSP) allowing neuronal networks to operate in functional ranges. Cell-wide or input-specific adaptations can be induced by pharmacological or genetic manipulations of activity, and by sensory deprivation. Reactive functional changes caused by deafferentation may partially share mechanisms with HSP. Acute hippocampal slices constitute a suitable model to investigate relatively rapid (hours) pathway-specific modifications occurring after denervation and explore the underlying mechanisms. As Schaffer collaterals constitute a major glutamatergic input to CA1 pyramidal neurons, we conducted whole-cell recordings of miniature excitatory postsynaptic currents (mEPSCs) to evaluate changes over 12 hours after slice preparation and CA3 dissection. We observed an increment in mEPSCs amplitude and a decrease in decay time, suggesting synaptic AMPA receptor upregulation and subunit content modifications. Sorting mEPSC by rise time, a correlate of synapse location along dendrites, revealed amplitude raises at two separate domains. A specific frequency increase was observed in the same domains and was accompanied by a global, unspecific raise. Amplitude and frequency increments were lower at sites initially more active, consistent with local compensatory processes. Transient preincubation with a specific Ca2+/calmodulin-dependent kinase II (CaMKII) inhibitor either blocked or occluded amplitude and frequency upregulation in different synapse populations. Results are consistent with the concurrent development of different known CaMKII-dependent HSP processes. Our observations support that deafferentation causes rapid and diverse compensations resembling classical slow forms of adaptation to inactivity. These results may contribute to understand fast-developing homeostatic or pathological events after brain injury.


title: Learning enhances behaviorally relevant representations in apical dendrites

abstract: Learning alters cortical representations and improves perception. Apical tuft dendrites in Layer 1, which are unique in their connectivity and biophysical properties, may be a key site of learning-induced plasticity. We used both two-photon and SCAPE microscopy to longitudinally track tuft-wide calcium spikes in apical dendrites of Layer 5 pyramidal neurons as mice learned a tactile behavior. Mice were trained to discriminate two orthogonal directions of whisker stimulation. Reinforcement learning, but not repeated stimulus exposure, enhanced tuft selectivity for both directions equally, even though only one was associated with reward. Selective tufts emerged from initially unresponsive or low-selectivity populations. Animal movement and choice did not account for changes in stimulus selectivity. Enhanced selectivity persisted even after rewards were removed and animals ceased performing the task. We conclude that learning produces long-lasting realignment of apical dendrite tuft responses to behaviorally relevant dimensions of a task.


title: Combining dictionary- and rule-based approximate entity linking with tuned BioBERT

abstract: Chemical named entity recognition (NER) is a significant step for many downstream applications like entity linking for the chemical text-mining pipeline. However, the identification of chemical entities in a biomedical text is a challenging task due to the diverse morphology of chemical entities and the different types of chemical nomenclature. In this work, we describe our approach that was submitted for BioCreative version 7 challenge Track 2, focusing on the  Chemical Identification task for identifying chemical entities and entity linking, using MeSH. For this purpose, we have applied a two-stage approach as follows (a) usage of fine-tuned BioBERT for identification of chemical entities (b) semantic approximate search in MeSH and PubChem databases for entity linking. There was some friction between the two approaches, as our rule-based approach did not harmonise optimally with partially recognized words forwarded by the BERT component. For our future work, we aim to resolve the issue of the artefacts arising from BERT tokenizers and develop joint learning of chemical named entity recognition and entity linking using pre-trained transformer-based models and compare their performance with our preliminary approach. Next, we will improve the efficiency of our approximate search in reference databases during entity linking. This task is non-trivial as it entails determining similarity scores of large sets of trees with respect to a query tree. Ideally, this will enable flexible parametrization and rule selection for the entity linking search.


title: Solanum galapagense-derived purple tomato fruit color is conferred by novel alleles of the Anthocyanin fruit and atroviolacium loci

abstract:
One hypothesis for the origin of endemic species of tomato on the Galapagos islands postulates a hybridization of Solanum pimpinellifolium and S. habrochaites. S. galapagense accession LA1141 has purple fruit pigmentation which has previously been described in green-fruited wild tomatoes such as S. habrochaites. Characterization of LA1141 derived purple pigmentation provides a test of the hybridization hypothesis. Purple pigmentation was recovered in progenies derived from LA1141 and the anthocyanins malvidin 3(coumaroyl)rutinoside-5-glucoside, petunidin 3-(coumaroyl) rutinoside-5-glucoside, and petunidin 3-(caffeoyl)rutinoside-5-glucoside were abundant. Fruit color was evaluated in an introgression population and three quantitative trait loci (QTLs) were mapped and validated in subsequent populations. The loci atroviolacium on chromosome 7, Anthocyanin fruit on chromosome 10, and uniform ripening also on chromosome 10, underly these QTLs. Sequence analysis suggested that the LA1141 alleles of Aft and atv are unique relative to those previously described from S. chilense accession LA0458 and S. cheesmaniae accession LA0434, respectively. Phylogenetic analysis of the LA1141 Aft genomic sequence did not support a green-fruited origin and the locus clustered with members of the red-fruited tomato clade. The LA1141 allele of Aft is not the result of an ancient introgression and underlies a gain of anthocyanin pigmentation in the red-fruited clade.

HighlightAnthocyanin fruit and atroviolacium confer purple pigmentation in Solanum galapagense LA1141 confirming a mechanism described for green-fruited tomatoes. LA1141 alleles cluster with red-fruited homologs suggesting an independent gain of pigmentation.

category: plant biology


title: Identification of mRNAs that undergo stop codon readthrough in Arabidopsis thaliana

abstract:
A stop codon ensures termination of translation at a specific position on an mRNA. Sometimes, termination fails as translation machinery recognizes a stop codon as a sense codon. This leads to stop codon readthrough (SCR) resulting in the continuation of translation beyond the stop codon, generating protein isoforms with C-terminal extension. SCR has been observed in viruses, fungi, and multicellular organisms including mammals. However, SCR is largely unexplored in plants. In this study, we have analyzed ribosome profiling datasets to identify mRNAs that undergo SCR in Arabidopsis thaliana. Analyses of the ribosome density, ribosome coverage and three-nucleotide periodicity of the ribosome profiling reads, in the mRNA region downstream of the stop codon, provided strong evidence for SCR in mRNAs of 144 genes. This process generates putative peroxisomal targeting signal, nuclear localization signal, prenylation signal, transmembrane helix and intrinsically disordered regions in the C-terminal extension of several of these proteins. Gene ontology (GO) functional enrichment analysis revealed that these 144 genes belong to three major functional groups - translation, photosynthesis and abiotic stress tolerance. Finally, using a luminescence-based assay, we experimentally demonstrate SCR in representative mRNAs belonging to these functional classes. Based on these observations, we propose that SCR plays an important role in plant physiology by regulating the protein localization and function.

AUTHOR SUMMARYProtein synthesis executed by macromolecular complexes, termed ribosomes, starts and stops at specific locations on a messenger RNA (mRNA). This fidelity is critical for the normal functioning of cells. However, sometimes ribosomes dont stop translation at the stop signal (termed stop codon) on an mRNA resulting in longer proteins with properties different from those of the canonical shorter protein. This process called stop codon readthrough (SCR) has been observed in viruses, fungi, and multicellular organisms including mammals. However, it remains largely unexplored in plants. In this study, we report evidence of SCR in 144 genes of Arabidopsis thaliana, a small flowering weed widely used as a model system to study plant biology. These genes are involved in protein synthesis, photosynthesis and stress tolerance in plants. We have also experimentally demonstrated SCR in a few genes that represent these functional classes. Our analysis shows that SCR can change the localization and functional properties of these proteins. We propose that SCR plays an important role in plant physiology.


title: Compositional Restricted Boltzmann Machines Unveil the Brain-Wide Organization of Neural Assemblies

abstract: Patterns of endogenous activity in the brain reflect a stochastic exploration of the neuronal state space that is constrained by the underlying assembly organization of neurons. Yet it remains to be shown that this interplay between neurons and their assembly dynamics indeed suffices to generate whole-brain data statistics. Here we recorded the activity from ~ 40, 000 neurons simultaneously in zebrafish larvae, and show that a data-driven network model of neuron-assembly interactions can accurately reproduce the mean activity and pairwise correlation statistics of their spontaneous activity. This model, the compositional Restricted Boltzmann Machine, unveils ~ 200 neural assemblies, which compose neurophysiological circuits and whose various combinations form successive brain states. From this, we mathematically derived an interregional functional connectivity matrix, which is conserved across individual animals and correlates well with structural connectivity. This novel, assembly-based generative model of brain-wide neural dynamics enables physiology-bound perturbation experiments in silico.


title: Control of cortical cytoskeleton-membrane interaction by RhoA regulates peripheral nerve myelination

abstract: Bidirectional transmission of mechanical and biochemical signals is integral to cell-environment communication and underlies the function of Schwann cells, the myelinating glia of the peripheral nervous system. As major integrators of "outside-in" signaling, Rho GTPases link actin cytoskeleton dynamics with cellular architecture to regulate adhesion and cell deformation. Using Schwann cell-specific gene inactivation, we discovered that RhoA promotes the initiation of myelination, axonal wrapping and axial spreading of Schwann cells, and is later required to restrict myelin growth in peripheral nerves. These effects are mediated by modulation of actomyosin contractility, actin dynamics and cortical actin-membrane attachment, which collectively couple tensional forces to intracellular signaling that regulate axon-Schwann cell interaction and myelin synthesis. This work establishes RhoA as an intrinsic regulator of a biomechanical response that controls the switch of Schwann cells towards the myelinating and the homeostatic states.


title: Fascicles split or merge every ~560 microns within the human cervical vagus nerve

abstract: 1Vagus nerve stimulation (VNS) is FDA approved for stroke rehabilitation, epilepsy, and depression; however, the vagus functional anatomy underlying the implant is poorly understood. We used microCT to quantify fascicular structure and neuroanatomy within human cervical vagus nerves. Fascicles split or merged every ~560 m (17.8 {+/-} 6.1 events/cm). The high degree of fascicular splitting and merging in humans may explain the clinical heterogeneity in patient responses.


title: Fascicles Split or Merge Every ~560 Microns Within the Human Cervical Vagus Nerve


title: Clinically relevant SMAC mimetics do not enhance human T cell proliferation or cytokine production

abstract: Secondary mitochondria-derived activator of caspases (SMAC) mimetics are being tested in dozens of clinical trials to treat cancer. These targeted therapies mimic endogenous molecules that promote apoptosis by antagonizing inhibitors of apoptosis (IAPs), which are commonly overexpressed in cancer cells. In T cells, IAPs function to restrain non-canonical NF-kB signaling. Thus, it has been suggested that in addition to their direct anti-cancer mechanism of action, SMAC mimetics may activate T cells, thereby promoting anti-tumor immunity. Here, we tested the effect of three clinically relevant SMAC mimetics on the proliferation and activation of primary human T cells. As previously reported, SMAC mimetics killed tumor cells and activated non-canonical NF-kB in T cells at clinically relevant doses. Surprisingly, none of the SMAC mimetics augmented T cell proliferation or effector function. These results question the assumption that SMAC mimetics are likely to boost anti-tumor immunity in cancer patients.


title: A myosin chaperone, UNC-45A, is a novel regulator of intestinal epithelial barrier integrity and repair

abstract: The actomyosin cytoskeleton serves as a key regulator of the integrity and remodeling of epithelial barriers by controlling assembly and functions of intercellular junctions and cell-matrix adhesions. While biochemical mechanisms that regulate activity of non-muscle myosin II (NM-II) in epithelial cells have been extensively investigated, little is known about assembly of the contractile myosin structures at the epithelial adhesion sites. UNC-45A is a cytoskeletal chaperone that is essential for proper folding of NM II heavy chains and myofilament assembly. We found abundant expression of UNC-45A in human intestinal epithelial cell (IEC) lines and in the epithelial layer of the normal human colon. Interestingly, protein levels of UNC-45A were decreased in colonic epithelium of patients with ulcerative colitis. CRISPR/Cas9-mediated knock-out of UNC-45A in HT-29 and SK-CO15 IEC disrupted epithelial barrier integrity, impaired assembly of epithelial adherence and tight junctions and attenuated cell migration. Consistently, decreased UNC-45 expression increased permeability of the Drosophila gut in vivo. The mechanisms underlying barrier disruptive and anti-migratory effects of UNC-45A depletion involved disorganization of the actomyosin bundles at epithelial junctions and the migrating cell edge. Loss of UNC-45A also decreased contractile forces at epithelial junctions and matrix adhesions. Expression of deletion mutants revealed roles for the myosin binding domain of UNC-45A in controlling IEC junctions and motility. Our findings uncover a novel mechanism that regulates integrity and restitution of the intestinal epithelial barrier, which may be impaired during mucosal inflammation.


title: The C. elegans TspanC8 tetraspanin TSP-14 exhibits isoform-specific localization and function

abstract:
Tetraspanin proteins are a unique family of highly conserved four-pass transmembrane proteins in metazoans. While much is known about their biochemical properties, the in vivo functions and distribution patterns of different tetraspanin proteins are less understood. Previous studies have shown that two paralogous tetraspanins that belong to the TspanC8 subfamily, TSP-12 and TSP-14, function redundantly to promote both Notch signaling and bone morphogenetic protein (BMP) signaling in C. elegans. TSP-14 has two isoforms, TSP-14A and TSP-14B, where TSP-14B has an additional 24 amino acids at its N-terminus compared to TSP-14A. By generating isoform specific knock-ins and knock-outs using CRISPR, we found that TSP-14A and TSP-14B share distinct as well as overlapping expression patterns and functions. While TSP-14A functions redundantly with TSP-12 to regulate body size and embryonic and vulva development, TSP-14B primarily functions redundantly with TSP-12 to regulate postembryonic mesoderm development. Importantly, TSP-14A and TSP-14B exhibit distinct subcellular localization patterns. TSP-14A is localized apically and on early and late endosomes. TSP-14B is localized to the basolateral cell membrane. We further identified a di-leucine motif within the N-terminal 24 amino acids of TSP-14B that serves as a basolateral membrane targeting sequence, and showed that the basolateral membrane localization of TSP-14B is important for its function. Our work highlights the diverse and intricate functions of TspanC8 tetraspanins in C. elegans, and demonstrates the importance of dissecting the functions of these important proteins in an intact living organism.

Author summaryTetraspanin proteins are a unique family of highly conserved four-pass transmembrane proteins in higher eukaryotes. Abnormal expression of certain tetraspanins is associated with various types of diseases, including cancer. Understanding the functions of different tetraspanin proteins in vivo is crucial in deciphering the link between tetraspanins and their associated disease states. We have previously identified two tetraspanins, TSP-12 and TSP-14, that share redundant functions in regulating multiple aspects of C. elegans development. Here we show that TSP-14 has two protein isoforms. Using CRISPR knock-in and knock-out technology, we have found that the two isoforms share unique, as well as overlapping expression patterns and functions. Furthermore, they exhibit distinct subcellular localization patterns. Our work highlights the diverse and intricate functions of tetraspanin proteins in a living multicellular organism, and demonstrates that protein isoforms are another mechanism C. elegans uses to increase the diversity and versatility of its proteome.


title: Large cells activate global protein degradation to maintain cell size homeostasis

abstract: Proliferating animal cells maintain a stable size distribution over generations despite fluctuations in cell growth and division size. This tight control of cell size involves both cell size checkpoints (e.g., delaying cell cycle progression for small cells) and size-dependent compensation in rates of mass accumulation (e.g., slowdown of cellular growth in large cells). We previously identified that the mammalian cell size checkpoint is mediated by a selective activation of the p38 MAPK pathway in small cells. However, mechanisms underlying the size-dependent compensation of cellular growth remain unknown. In this study, we quantified global rates of protein synthesis and degradation in naturally large and small cells, as well as in conditions that trigger a size-dependent compensation in cellular growth. Rates of protein synthesis increase proportionally with cell size in both perturbed and unperturbed conditions, as well as across cell cycle stages. Additionally, large cells exhibit elevated rates of global protein degradation and increased levels of activated proteasomes. Conditions that trigger a large-size-induced slowdown of cellular growth also promote proteasome-mediated global protein degradation, which initiates only after growth rate compensation occurs. Interestingly, the elevated rates of global protein degradation in large cells were disproportionately higher than the increase in size, suggesting activation of protein degradation pathways. Large cells at the G1/S transition show hyperactivated levels of protein degradation, even higher than similarly sized or larger cells in S or G2, coinciding with the timing of the most stringent size control in animal cells. Together, these findings suggest that large cells maintain cell size homeostasis by activating global protein degradation to induce a compensatory slowdown of growth.


title: Tropical forest dynamics correspond to fair games in economic theory of financial markets

abstract: Ecological and economic systems both comprise of autonomous adaptive agents. It is thus possible that similar mechanisms determine the organization of both these complex systems. Indeed several economic theories have already been successfully applied in an ecological context. Here we show that  efficient market theory in economics, where future earnings are distributed between competitors by a  fair game, corresponds to fitness-equalizing mechanisms of coexistence in ecology. In contrast to stabilizing mechanisms, which promote coexistence by giving each species an equilibrium abundance that is resilient to perturbations, equalizing mechanisms promote coexistence without such resilience by minimizing the net fitness differences between species. However, identifying stabilizing and equalizing mechanisms from the short time-series data that are typically available in ecology is challenging. We used techniques from economics that are applied to collections of short time-series from a system. We found that observed species abundance dynamics in a neotropical forest are generally in agreement with efficient market theory implying a dominant role of equalizing mechanisms, which finding quantifies and supports what was generally believed about that specific forest system. Our study highlights that complex systems from ecology and economics share common features suggesting the possibility of further synergy between ecology and economics in future.


title: A theoretical framework for multi-species range expansion in spatially heterogeneous landscapes

abstract: Range expansion is the spatial spread of a population into previously unoccupied regions. Understanding range expansion is important for the study and successful manipulation and management of ecosystems, with applications ranging from controlling bacterial biofilm formation in industrial and medical environments to large scale conservation programmes for species undergoing climate-change induced habitat disruption. During range expansion, species typically encounter competitors. Moreover, the environment into which expansion takes place is almost always heterogeneous when considered at the scale of the individual. Despite the ubiquitous nature of these features, the impact of competition and spatial landscape heterogeneities on range expansion remains understudied. In this paper we present a theoretical framework comprising two competing generic species undergoing range expansion and use it to investigate the impact of spatial landscape heterogeneities on range expansion with a particular focus on its effect on competition dynamics. We reveal that the area covered by range expansion during a fixed time interval is highly variable due to the fixed landscape heterogeneities. Moreover, we report significant variability in competitive outcome (relative abundance of a focal species) but determine that this is induced by low initial population densities, independent of landscape heterogeneities. We further show that both area covered by range expansion and competitive outcome can be accurately predicted by a Voronoi tessellation with respect to an appropriate metric, which only requires information on the spatial landscape and the response of each species to that landscape. Finally, we reveal that if species interact antagonistically during range expansion, the dominant mode of competition depends on the initial population density. Antagonistic actions determine competitive outcome if the initial population density is high, but competition for space is the dominant mode of competition if the initial population density is low.


title: Transcriptome innovations in primates revealed by single-molecule long-read sequencing

abstract: Transcriptomic diversity greatly contributes to the fundamentals of disease, lineage-specific biology, and environmental adaptation. However, much of the actual isoform repertoire contributing to shaping primate evolution remains unknown. Here, we combined deep long- and short-read sequencing complemented with mass spectrometry proteomics in a panel of lymphoblastoid cell lines (LCLs) from human, three other great apes, and rhesus macaque, producing the largest full-length isoform catalog in primates to date. Our transcriptomes reveal thousands of novel transcripts, some of them under active translation, expanding and completing the repertoire of primate gene models. Our comparative analyses unveil hundreds of transcriptomic innovations and isoform usage changes related to immune function and immunological disorders. The confluence of these innovations with signals of positive selection and their limited impact in the proteome points to changes in alternative splicing in genes involved in immune response as an important target of recent regulatory divergence in primates.


title: Disentangling the effects of jasmonate and tissue loss on the sex allocation of an annual plant

abstract: Selection through pollinators plays a major role in the evolution of reproductive traits. However, herbivory can also induce changes in plant sexual expression and sexual systems, potentially influencing conditions governing transitions between sexual systems. Previous work has shown that herbivory has a strong effect on sex allocation in the wind-pollinated annual plant Mercurialis annua, likely mediated by resource loss. It is also known that many plants respond to herbivory by inducing signalling, and endogenous responses to it, via the plant hormone jasmonate. Here, we attempt to uncouple the effects of herbivory on sex allocation in M. annua through resource limitation (tissue loss) versus plant responses to jasmonate hormone signalling. We used a two-factorial experiment with four treatment combinations: control, herbivory (25% chronic tissue loss), jasmonate, and combined herbivory and jasmonate. We estimated the effects of tissue loss and defence-inducing hormones on reproductive allocation, male reproductive effort, and sex allocation. Tissue loss caused plants to reduce their male reproductive effort, resulting in changes in combined sex allocation. However, application of jasmonate after herbivory reversed its effect on male investment. Our results show that herbivory has consequences on plant sex expression and sex allocation, and that defence-related hormones such as jasmonate can buffer the impacts. We discuss the physiological mechanisms that might underpin the effects of herbivory on sex allocation, and their potential implications for the evolution of plant sexual systems.


title: Physiological and life history changes associated with seasonal adaptation in the cactophilic Drosophila mojavensis

abstract: Many insects inhabiting temperate climates are faced with changing environmental conditions throughout the year. Depending on the species, these environmental fluctuations can be experienced within a single generation or across multiple generations. Strategies for dealing with these seasonal changes vary across populations. Drosophila mojavensis is a cactophilic Drosophila species endemic to the Sonoran Desert. The Sonoran Desert regularly reaches temperatures of 50{degrees}C in the summer months. As individuals of this population are rare to collect in the summer months, we therefore simulated in a temperature and light controlled chamber the cycling temperatures experienced by D. mojavensis in the Sonoran Desert from April to July (four generations) to understand the physiological and life history changes that allow this population to withstand these conditions. In contrast to our hypothesis of a summer aestivation, we found that D. mojavensis continue to reproduce during the summer months, albeit with lower viability, but the longevity of the population is highly reduced during this period. As expected, stress resistance increased during the summer months in both the adult and the larval stages. This study examines several strategies for withstanding the Sonoran Desert summer conditions which may be informative in the study of other desert endemic species.


title: SARS-CoV-2 ORF8 encoded protein contains a histone mimic, disrupts chromatin regulation, and enhances replication

abstract: SARS-CoV-2 emerged in China at the end of 2019 and caused the global pandemic of COVID-19, a disease with high morbidity and mortality. While our understanding of this new virus is rapidly increasing, gaps remain in our understanding of how SARS-CoV-2 can effectively suppress host cell antiviral responses. Recent work on other viruses has demonstrated a novel mechanism through which viral proteins can mimic critical regions of human histone proteins. Histone proteins are responsible for governing genome accessibility and their precise regulation is critical for a cells ability to control transcription and respond to viral threats. Here, we show that the protein encoded by ORF8 (Orf8) in SARS-CoV-2 functions as a histone mimic of the ARKS motif in histone 3. Orf8 is associated with chromatin, binds to numerous histone-associated proteins, and is itself acetylated within the histone mimic site. Orf8 expression in cells disrupts multiple critical histone post-translational modifications (PTMs) including H3K9ac, H3K9me3, and H3K27me3 and promotes chromatin compaction while Orf8 lacking the histone mimic motif does not. Further, SARS-CoV-2 infection in human cell lines and postmortem patient lung tissue cause these same disruptions to chromatin. However, deletion of the Orf8 gene from SARS-CoV-2 largely blocks its ability to disrupt host-cell chromatin indicating that Orf8 is responsible for these effects. Finally, deletion of the ORF8 gene affects the host-cell transcriptional response to SARS-CoV-2 infection in multiple cell types and decreases the replication of SARS-CoV-2 in human induced pluripotent stem cell-derived lung alveolar type 2 (iAT2) pulmonary cells. These findings demonstrate a novel function for the poorly understood ORF8-encoded protein and a mechanism through which SARS-CoV-2 disrupts host cell epigenetic regulation. Finally, this work provides a molecular basis for the finding that SARS-CoV-2 lacking ORF8 is associated with decreased severity of COVID-19.


title: Fast anther dehiscence state recognition system establishing by deep learning to screen heat tolerant cotton

abstract:
Cotton is one of the most economically important crops in the world. The fertility of male reproductive organs is a key determinant of cotton yield. The anther dehiscence or indehiscence directly determine the probability of fertilization in cotton. Thus, the rapid and accurate identification of cotton anther dehiscence status is important for judging anther growth status and promoting genetic breeding research. The development of computer vision technology and the advent of big data have prompted the application of deep learning techniques to agricultural phenotype research. Therefore, two deep learning models (Faster R-CNN and YOLOv5) were proposed to detect the number and dehiscence status of anthers. The single-stage model based on YOLOv5 has higher recognition efficiency and the ability to deploy to the mobile end. Breeding researchers can apply this model to terminals to achieve a more intuitive understanding of cotton anther dehiscence status. Moreover, three improvement strategies of Faster R-CNN model were proposed, the improved model has higher detection accuracy than YOLOv5 model. In addition, the percentage of dehiscent anther of randomly selected 30 cotton varieties were observed from cotton population under normal temperature and high temperature (HT) conditions through the integrated Faster R-CNN model and manual observation. The result showed HT varying decreased the percentage of dehiscent anther in different cotton lines, consistent with the manual method. Thus, this system can help us to rapid and accurate identification of HT-tolerant cotton.

One sentence summaryThe deep learning technique was applied to identify the anther dehiscence state for the first time to quickly screen heat tolerant cotton varieties and help to explore key genetic improvement genes.


title: FLIP: Benchmark tasks in fitness landscape inference for proteins

abstract: Machine learning could enable an unprecedented level of control in protein engineering for therapeutic and industrial applications. Critical to its use in designing proteins with desired properties, machine learning models must capture the protein sequence-function relationship, often termed fitness landscape. Existing bench-marks like CASP or CAFA assess structure and function predictions of proteins, respectively, yet they do not target metrics relevant for protein engineering. In this work, we introduce Fitness Landscape Inference for Proteins (FLIP), a benchmark for function prediction to encourage rapid scoring of representation learning for protein engineering. Our curated tasks, baselines, and metrics probe model generalization in settings relevant for protein engineering, e.g. low-resource and extrapolative. Currently, FLIP encompasses experimental data across adeno-associated virus stability for gene therapy, protein domain B1 stability and immunoglobulin binding, and thermostability from multiple protein families. In order to enable ease of use and future expansion to new tasks, all data are presented in a standard format. FLIP scripts and data are freely accessible at https://benchmark.protein.properties.


title: Effects of tendon viscoelasticity in the distribution of forces over sutures in a model tendon-to-bone repair

abstract: Tears to the rotator cuff often require surgical repair. These repairs often culminate in re-tearing when sutures break through the tendon in the weeks following repair. Although numerous studies have been performed to identify suturing strategies that reduce this risk by balancing forces across sutures, none have accounted for how the viscoelastic nature of tendon influences load sharing. With the aim of providing insight into this problem, we studied how tendon viscoelasticity, tendon stiffness, and suture anchor spacing affect this balancing of forces across sutures. Results from a model of a three-row sutured re-attachment demonstrated that optimized distributions of suture stiffnesses and of the spacing of suture anchors can balance the forces across sutures to within a few percent, even when accounting for tendon viscoelasticity. Non-optimized distributions resulted in concentrated force, typically in the outermost sutures. Results underscore the importance of accounting for viscoelastic effects in the design of tendon to bone repairs.


title: A Transparent Ultrasound Array for Real-time Optical, Ultrasound and Photoacoustic Imaging

abstract:
Objective and Impact StatementSimultaneous imaging of ultrasound and optical contrasts can help map structural, functional and molecular biomarkers inside living subjects with high spatial resolution. There is a need to develop a platform to facilitate this multimodal imaging capability to improve diagnostic sensitivity and specificity.

IntroductionCurrently, combining ultrasound, photoacoustic and optical imaging modalities is challenging because con-ventional ultrasound transducer arrays are optically opaque. As a result, complex geometries are used to co-align both optical and ultrasound waves in the same field of view.

MethodsOne elegant solution is to make the ultrasound transducer transparent to light. Here, we demonstrate a novel transparent ultrasound transducer (TUT) liner array fabricated using a transparent lithium niobate piezoelectric material for real-time multimodal imaging.

ResultsThe TUT array consisted of 64 elements and centered at [~] 6 MHz frequency. We demonstrate a quad-mode ultrasound, Doppler ultrasound, photoacoustic and fluorescence imaging in real-time using the TUT array directly coupled to the tissue mimicking phantoms.

ConclusionThe TUT array successfully showed a multimodal imaging capability, and has potential applications in diagnosing cancer, neuro and vascular diseases, including image-guided endoscopy and wearable imaging.


title: Characterization of scar tissue biomechanics during adult murine flexor tendon healing

abstract: Tendon injuries are very common and result in significant impairments in mobility and quality of life. During healing, tendons produce a scar at the injury site, characterized by abundant and disorganized extracellular matrix and by permanent deficits in mechanical integrity compared to healthy tendon. Although a significant amount of work has been done to understand the healing process of tendons and to develop potential therapeutics for tendon regeneration, there is still a significant gap in terms of assessing the direct effects of therapeutics on the functional and material quality specifically of the scar tissue, and thus, on the overall tendon healing process. In this study, we focused on characterizing the mechanical properties of only the scar tissue in flexor digitorum longus (FDL) tendons during the proliferative and remodeling healing phases and comparing these properties with the mechanical properties of the composite healing tissue. Our method was sensitive enough to identify significant differences in structural and material properties between the scar and tendon-scar composite tissues. To account for possible inaccuracies due to the small aspect ratio of scar tissue, we also applied inverse finite element analysis (iFEA) to compute mechanical properties based on simulated tests with accurate specimen geometries and boundary conditions. We found that the scar tissue linear tangent moduli calculated from iFEA were not significantly different from those calculated experimentally at all healing timepoints, validating our experimental findings, and suggesting the assumptions in our experimental calculations were accurate. Taken together, this study first demonstrates that due to the presence of uninjured stubs, testing composite healing tendons without isolating the scar tissue overestimates the material properties of the scar itself. Second, our scar isolation method promises to enable more direct assessment of how different treatment regimens (e.g., cellular ablation, biomechanical and/or biochemical stimuli, tissue engineered scaffolds) affect scar tissue function and material quality in multiple different types of tendons.


title: Imaging the Extent and Location of Spatiotemporally Distributed Epileptiform Sources from MEG Measurements

abstract: Non-invasive MEG/EEG source imaging provides valuable information about the epileptogenic brain areas which can be used to aid presurgical planning in focal epilepsy patients suffering from drug-resistant seizures. However, the source extent estimation for electrophysiological source imaging remains to be a challenge and is usually largely dependent on subjective choice. Our recently developed algorithm, fast spatiotemporal iteratively reweighted edge sparsity minimization (FAST-IRES) strategy, has been shown to objectively estimate extended sources from EEG recording, while it has not been applied to MEG recordings. In this work, through extensive numerical experiments and real data analysis in a group of focal drug-resistant epilepsy patients interictal spikes, we demonstrated the ability of FAST-IRES algorithm to image the location and extent of underlying epilepsy sources from MEG measurements. Our results indicate the merits of FAST-IRES in imaging the location and extent of epilepsy sources for pre-surgical evaluation from MEG measurements.


title: Predicting direct physical interactions in multimeric proteins with deep learning

abstract: Accurate descriptions of protein-protein interactions are essential for understanding biological systems. Remarkably accurate atomic structures have been recently computed for individual proteins by AlphaFold2 (AF2). Here, we demonstrate that the same neural network models from AF2 developed for single protein sequences can be adapted to predict the structures of multimeric protein complexes without retraining. In contrast to common approaches, our method, AF2Complex, does not require paired multiple sequence alignments. It achieves higher accuracy than some complex protein-protein docking strategies and provides a significant improvement over AF-Multimer, a new development of AlphaFold for multimeric proteins. Moreover, we introduce metrics for predicting direct protein-protein interactions between arbitrary protein pairs and validate AF2Complex on some challenging benchmark sets and the E. coli proteome. Lastly, using the cytochrome c biogenesis system I as an example, we present high-confidence models of three sought-after assemblies formed by eight members of this system.


title: Weakly-Supervised Tumor Purity Prediction FromFrozen H&E Stained Slides

abstract: Estimating tumor purity is especially important in the age of precision medicine. Purity estimates have been shown to be critical for correction of tumor sequencing results, and higher purity samples allow for more accurate interpretations from next-generation sequencing results. In addition, tumor purity has been shown to be correlated with survival outcomes for several diseases. Molecular-based purity estimates using computational approaches require sequencing of tumors, which is both time-consuming and expensive. Here we propose an approach, weakly-supervised purity (wsPurity), which can accurately quantify tumor purity within a slide, using multiple and different types of cancer. This approach allows for a flexible analysis of tumors from whole slide imaging (WSI) of histology hematoxylin and eosin (H&E) slides. Our model predicts tumor type with high accuracy (greater than 80% on an independent test cohort), and tumor purity at a higher accuracy compared to a comparable fully-supervised approach (0.1335 MAE on an independent test cohort). In addition to tumor purity prediction, our approach can identify high resolution tumor regions within a slide, to enrich tumor cell selection for downstream analyses. This model could also be used in a clinical setting, to stratify tumors into high and low tumor purity, using different thresholds, in a cancer-dependent manner, depending on what purity levels correlate with worse disease outcomes. In addition, this approach could be used in clinical practice to select the best tissue block for sequencing. Overall, this approach can be used in several different ways to analyze WSIs of tumor H&E sections.


title: Jointly leveraging spatial transcriptomics and deep learning models for pathology image annotation improves cell type identification over either approach alone.

abstract: Spatial transcriptomics technologies have recently emerged as a powerful tool for measuring spatially resolved gene expression directly in tissues sections, revealing cell types and their dysfunction in unprecedented detail. However, spatial transcriptomics technologies are limited in their ability to separate transcriptionally similar cell types and can suffer further difficulties identifying cell types in slide regions where transcript capture is low. Here, we describe a conceptually novel methodology that can computationally integrate spatial transcriptomics data with cell-type-informative paired tissue images, obtained from, for example, the reverse side of the same tissue section, to improve inferences of tissue cell type composition in spatial transcriptomics data. The underlying statistical approach is generalizable to any spatial transcriptomics protocol where informative paired tissue images can be obtained. We demonstrate a use case leveraging cell-type-specific immunofluorescence markers obtained on mouse brain tissue sections and a use case for leveraging the output of AI annotated H&E tissue images, which we used to markedly improve the identification of clinically relevant immune cell infiltration in breast cancer tissue. Thus, combining spatial transcriptomics data with paired tissue images has the potential to improve the identification of cell types and hence to improve the applications of spatial transcriptomics that rely on accurate cell type identification.


title: Cell type identification in spatial transcriptomics data can be improved by leveraging cell-type-informative paired tissue images using a Bayesian probabilistic model.


title: Lossless Indexing with Counting de Bruijn Graphs

abstract: Sequencing data is rapidly accumulating in public repositories. Making this resource accessible for interactive analysis at scale requires efficient approaches for its storage and indexing. There have recently been remarkable advances in building compressed representations of annotated (or colored) de Bruijn graphs for efficiently indexing k-mer sets. However, approaches for representing quantitative attributes such as gene expression or genome positions in a general manner have remained underexplored. In this work, we propose Counting de Bruijn graphs (Counting DBGs), a notion generalizing annotated de Bruijn graphs by supplementing each node-label relation with one or many attributes (e.g., a k-mer count or its positions). Counting DBGs index k-mer abundances from 2,652 human RNA-Seq samples in over 8-fold smaller representations compared to state-of-the-art bioinformatics tools and yet faster to construct and query. Furthermore, Counting DBGs with positional annotations losslessly represent entire reads in indexes on average 27% smaller than the input compressed with gzip for human Illumina RNA-Seq and 57% smaller for PacBio HiFi sequencing of viral samples. A complete searchable index of all viral PacBio SMRT reads from NCBIs SRA (152,884 samples, 875 Gbp) comprises only 178 GB. Finally, on the full RefSeq collection, we generate a lossless and fully queryable index that is 4.4-fold smaller than the MegaBLAST index. The techniques proposed in this work naturally complement existing methods and tools employing de Bruijn graphs and significantly broaden their applicability: from indexing k-mer counts and genome positions to implementing novel sequence alignment algorithms on top of highly compressed graph-based sequence indexes.


title: Scalable estimation of microbial co-occurrence networks with Variational Autoencoders

abstract: Estimating microbe-microbe interactions is critical for understanding the ecological laws governing microbial communities. Rapidly decreasing sequencing costs have promised new opportunities to estimate microbe-microbe interactions across thousands of uncultured, unknown microbes. However, typical microbiome datasets are very high dimensional and accurate estimation of microbial correlations requires tens of thousands of samples, exceeding the computational capabilities of existing methodologies. Furthermore, the vast majority of microbiome studies collect compositional metagenomics data which enforces a negative bias when computing microbe-microbe correlations. The Multinomial Logistic Normal (MLN) distribution has been shown to be effective at inferring microbe-microbe correlations, however scalable Bayesian inference of these distributions has remained elusive. Here, we show that carefully constructed Variational Autoencoders (VAEs) augmented with the Isometric Log-ratio (ILR) transform can estimate low-rank MLN distributions thousands of times faster than existing methods. These VAEs can be trained on tens of thousands of samples, enabling co-occurrence inference across tens of thousands of microbes without regularization. The latent embedding distances computed from these VAEs are competitive with existing beta-diversity methods across a variety of mouse and human microbiome classification and regression tasks, with notable improvements on longitudinal studies.


title: Deciphering the language of antibodies using self-supervised learning

abstract: An individuals B cell receptor (BCR) repertoire encodes information about past immune responses, and potential for future disease protection. Deciphering the information stored in BCR sequence datasets will transform our fundamental understanding of disease and enable discovery of novel diagnostics and antibody therapeutics. One of the grand challenges of BCR sequence analysis is the prediction of BCR properties from their amino acid sequence alone. Here we present an antibody-specific language model, AntiBERTa, which provides a contextualised representation of BCR sequences. Following pre-training, we show that AntiBERTa embeddings learn biologically relevant information, generalizable to a range of applications. As a case study, we demonstrate how AntiBERTa can be fine-tuned to predict paratope positions from an antibody sequence, outperforming public tools across multiple metrics. To our knowledge, AntiBERTa is the deepest protein family-specific language model, providing a rich representation of BCRs. AntiBERTa embeddings are primed for multiple downstream tasks and can improve our understanding of the language of antibodies.


title: Unsupervised integration of single-cell multi-omics datasets with disparities in cell-type representation

abstract:
Integrated analysis of multi-omics data allows the study of how different molecular views in the genome interact to regulate cellular processes; however, with a few exceptions, applying multiple sequencing assays on the same single cell is not possible. While recent unsupervised algorithms align single-cell multi-omic datasets, these methods have been primarily benchmarked on co-assay experiments rather than the more common single-cell experiments taken from separately sampled cell populations. Therefore, most existing methods perform subpar alignments on such datasets. Here, we improve our previous work Single Cell alignment using Optimal Transport (SCOT) by using unbalanced optimal transport to handle disproportionate cell-type representation and differing sample sizes across single-cell measurements. We show that our proposed method, SCOTv2, consistently yields quality alignments on five real-world single-cell datasets with varying cell-type proportions and is computationally tractable. Additionally, we extend SCOTv2 to integrate multiple (M [≥] 2) single-cell measurements and present a self-tuning heuristic process to select hyperparameters in the absence of any orthogonal correspondence information.

Available at: http://rsinghlab.github.io/SCOT.