title: Joint inference of migration and reassortment patterns for viruses with segment genomes

abstract:
The structured coalescent allows inferring migration patterns between viral sub-populations from genetic sequence data. However, these analyses typically assume that no genetic recombination process impacted the sequence evolution of pathogens. For segmented viruses, such as influenza, that can undergo reassortment this assumption is broken. Reassortment reshuffles the segments of different parent lineages upon a coinfection event, which means that the shared history of viruses has to be represented by a network instead of a tree. Therefore, full genome analyses of such viruses is complex or even impossible. While this problem has been addressed for unstructured populations, it is still impossible to account for population structure, such as induced by different host populations, while also accounting for reassortmentWe address this by extending the structured coalescent to account for reassortment and present a framework for investigating possible ties between reassortment and migration (host jump) events. This method can accurately estimate sub-population dependent effective populations sizes, reassortment and migration rates from simulated data. Additionally, we apply the new model to avian influenza A/H5N1 sequences, sampled from two avian host types, Anseriformes and Galliformes. We contrast our results with a structured coalescent without reassortment inference, which assumes independently evolving segments. This reveals that taking into account segment reassortment and using sequencing data from several viral segments for joint phylodynamic inference leads to different estimates for effective population sizes, migration and clock rates.

This new model is implemented as the Structured Coalescent with Reassortment (SCoRe) package for BEAST 2.5 and is available at https://github.com/jugne/SCORE.

category: evolutionary biology


title: Loricarioid catfish evolved skin denticles that recapitulate teeth at the structural, developmental, and genetic levels

abstract: The first vertebrate mineralized skeleton was an external bony armor coated with dental structures. The subsequent emergence of a mineralized endoskeleton and of teeth are considered key innovations in the diversification of vertebrates. Although time clouds our understanding of the initial evolution of these mineralized structures, recent re-emergences may shed light on the underlying processes. Loricarioid catfishes are a lineage that, much like the ancestral vertebrates, bear denticle-clad bony armor from head to tail. Loricarioid denticles (LDs) and oral teeth are very similar in superstructure. We show here that other extra-oral dental structures are found as ancestral characters only in lineages that are distantly related to loricarioids such as sharks or coelacanth, indicating that LDs have independently re-emerged in loricarioid catfishes. We investigate whether the similarities between LDs and teeth extend to their developmental and genetic context, and how their development compares to that of other vertebrate integument structures. Our detailed study of the development of LDs, and gene expression analyses through in situ hybridization confirm that all 12 genes from the tooth-forming gene regulatory network (oGRN) are expressed in developing LDs in a similar way as they are expressed in developing teeth. We then compare the developmental, structural, and genetic aspects of LD and teeth with that of other integument appendages such as fish scales, shark dermal denticles, feathers and hairs. We find that LDs share all developmental cues with teeth and, to a lesser extent, with the other vertebrate integument structures. Taken together, our results indicate that denticles have re-emerged on the trunk of loricarioid catfishes through the ectopic co-option of the oGRN rather than the resurrection of an ancestral trunk-specific denticle genetic pathway.


title: Caveolin-3 Null Mutation in Family with Barretts Esophagus and Esophageal Adenocarcinoma

abstract:
INTRODUCTIONAggregation of Barretts esophagus (BE) and esophageal adenocarcinoma (EAC) in families has been termed familial Barretts esophagus (FBE). Analysis of single, large FBE families can enable the identification of genetic susceptibility to complex diseases such as BE and EAC.

METHODSPhenotypes of BE and EAC were ascertained in a large FBE family with 7 affected members: 4 men with EAC, 1 man with BE and high grade dysplasia, and 2 women with non-dysplastic BE by review of endoscopy and surgical pathology reports. Whole exome sequencing was performed on germline DNA from 3 affected members to identify variants in coding genes that segregated with disease. Formalin fixed paraffin embedded tissue from an affected family member as well as non-familial subjects with BE and EAC was examined with regular histology and immunohistochemistry. The CAV3 gene with a variant segregating in the family was further characterized in a porcine model of esophageal injury using immunofluorescence.

RESULTSUsing a whole exome sequencing approach on an exceptional FBE family we identified a segregating nonsense mutation in the gene Caveolin-3 (CAV3). Histologic examination of a formalin fixed paraffin embedded (FFPE) esophagectomy specimen from an individual carrying the CAV3 null mutation revealed esophageal submucosal glands (ESMG) that showed acinar metaplasia with marked atypia and absence of myoepithelial cells, distinctly different from acinar metaplasia seen in ESMG of non-familial subjects with BE and high grade dysplasia. Immunofluorescence studies of ESMG in porcine esophagus revealed the presence of CAV3 in selected cells in a distribution that was consistent with myoepithelial cells. Experimental injury of the porcine esophagus using radiofrequency ablation revealed that CAV3 expression increased markedly within ESMGs, ESMG ductal epithelium, and overlying healing neosquamous epithelium 10 days after injury.

CONCLUSIONSWe theorize that CAV3 expression, perhaps through myoepithelial cells within ESMGs, controls the differentiation and proliferation of squamous epithelial precursor cells in response to injury. Furthermore, the truncating nonsense CAV3 mutation discovered in a family disrupts normal squamous healing and the organization of ESMGs, making affected family members susceptible to the proliferation and development of metaplastic columnar BE and EAC.

category: genetics


title: Comparative analyses and phylogenetic relationships of 15 Trapa (Trapaceae) species based on Complete Chloroplast Genomes

abstract: Trapa L. is floating-leaved aquatic plants with important economic and ecological values. However, species identification and phylogenetic relationship are still unresolved for Trapa. In this study, complete chloroplast genomes of 13 Trapa species/taxa were sequenced and annotated. Combined with released sequences of the other two species, comparative analysis of cp genomes was first performed on the 15 Trapa species/taxa. The 15 cp genomes exhibited quadripartite structures with medium size of 155, 453-155, 559 bp. IR/SC junctions were conservative with no obvious change found. Long repetitive repeats and SSRs were mostly detected in the intergenic and LSC regions, providing useful plastid markers for species and relationship identification. Three phylogenetic analyses (MP, ML and BI) consistently showed two clusters within Trapa, including large- and small-seed species/taxa, respectively. This study provided the baseline information for phylogeography of Trapa, which would facilitate the management and utilization of genetic resources of the genus.

category: genomics


title: The Medaka Inbred Kiyosu-Karlsruhe (MIKK) Panel

abstract: Unraveling the relationship between genetic variation and phenotypic traits remains a fundamental challenge in biology. Mapping variants underlying complex traits while controlling for confounding environmental factors is often problematic. To address this, we have established a vertebrate genetic resource specifically to allow for robust genotype-to-phenotype investigations. The teleost medaka (Oryzias latipes) is an established genetic model system with a long history of genetic research and a high tolerance to inbreeding from the wild. Here we present the Medaka Inbred Kiyosu-Karlsruhe (MIKK) panel: the first near-isogenic panel of 80 inbred lines in a vertebrate model derived from a wild founder population. Inbred lines provide fixed genomes that are a prerequisite for the replication of studies, studies which vary both the genetics and environment in a controlled manner and functional testing. The MIKK panel will therefore enable phenotype-to-genotype association studies of complex genetic traits while allowing for careful control of interacting factors, with numerous applications in genetic research, human health, and drug development and fundamental biology. Here we present a detailed characterisation of the genetic variation across the MIKK panel, which provides a rich and unique genetic resource to the community by enabling large-scale experiments for mapping complex traits.


title: Chromosome-scale and haplotype-resolved genome assembly of a tetraploid potato cultivar

abstract: Potato is the most important tuber crop in the world. However, separate reconstruction of the four haplotypes of its autotetraploid genome remained an unsolved challenge. Here, we report the 3.1 Gb haplotype-resolved (at 99.6% precision), chromosome-scale assembly of the potato cultivar  Otava using high-quality long reads coupled with single-cell sequencing of 717 pollen genomes and Hi-C data. Unexpectedly, almost 50% of the genome were found to be identical-by-descent due to recent inbreeding, which contrasted by highly abundant structural rearrangements involving around 20% of the genome. Among 38,214 genes, only 54% were present in four haplotypes with an average of 3.2 copies per gene. Analyzing the leaf transcriptome as example, we found that 11% of the genes featured differently expressed alleles in at least one of the haplotypes, of which 25% are likely regulated through allele-specific DNA methylation. Our work sheds light on the recent breeding history of potato, the functional organization of its tetraploid genome and has the potential to strengthen the future of genomics-assisted breeding.


title: Genomic context sensitivity of insulator function

abstract: Compartmentalization of interactions between genomic regulatory elements and potential target genes is influenced by the binding of insulator proteins such as CTCF, which act as potent enhancer blockers when interposed between an enhancer and a promoter in a reporter assay. But only a minority of CTCF sites genome-wide function as boundary elements, depending on cellular and genomic context. To dissect the influence of genomic context on enhancer blocker activity, we integrated reporter constructs with promoter-only, promoter and enhancer, and enhancer blocker configurations at hundreds of thousands of genomic sites using the Sleeping Beauty transposase. Deconvolution of reporter activity by genomic position revealed strikingly different patterns of reporter function, including a compartment of enhancer blocker reporter integrations with robust expression. The high density of integration sites permits quantitative delineation of characteristic genomic context sensitivity profiles, and their decomposition into sensitivity to both local and distant DNaseI hypersensitive sites. Furthermore, a single-cell expression approach permits direct linkage of reporters integrated into the same clonal lineage with differential endogenous gene expression, revealing that CTCF insulator activity does not completely abrogate reporter effects on endogenous gene expression. Collectively, our results lend new insight to genomic regulatory compartmentalization and its influence on the determinants of promoter-enhancer specificity.


title: Error minimization and specificity could emerge in a genetic code as by-products ofprebiotic evolution

abstract: The emergence of the genetic code was a major transition in the evolution from a prebiotic RNA world to the earliest modern cells1. A prominent feature of the standard genetic code is error minimization, or the tendency of mutations to be unusually conservative in preserving biophysical features of the amino acid2-6. While error minimization is often assumed to result from natural selection, it has also been speculated that error minimization may be a by-product of emergence of the genetic code3. During establishment of the genetic code in an RNA world, self-aminoacylating ribozymes would enforce the mapping of amino acids to anticodons. Here we show that expansion of the genetic code, through co-option of ribozymes for new substrates, could result in error minimization as an emergent property. Using self-aminoacylating ribozymes previously identified during an exhaustive search of sequence space7, we measured the activity of thousands of candidate ribozymes on alternative substrates (activated analogs for tryptophan, phenylalanine, leucine, isoleucine, valine, and methionine). Related ribozymes exhibited preferences for biophysically similar substrates, indicating that co-option of existing ribozymes to adopt additional amino acids into the genetic code would itself lead to error minimization. Furthermore, ribozyme activity was positively correlated with specificity, indicating that selection for increased activity would also lead to increased specificity. These results demonstrate that by-products of the evolution and functional expansion of a ribozyme system could lead to adaptive properties of a genetic code. Such  spandrels could thus underlie significant prebiotic developments.

category: biochemistry


title: Identification of SSX2IP/Msd1 as a Wtip-binding partner by targeted proximity biotinylation

abstract: Wilms tumor-1-interacting protein (Wtip) is a LIM-domain-containing adaptor that links cell junctions with actomyosin complexes and modulates actomyosin contractility and ciliogenesis in Xenopus embryos. The Wtip C-terminus with three LIM domains binds binds Shroom3 and modulates Shroom3-induced apical constriction in ectoderm cells. We found that the N-terminal domain localizes to the basal bodies in skin multiciliated cells, but its interacting partners remain largely unknown. Using a novel targeted proximity biotinylation approach with anti-GFP antibody attached to the biotin ligase BirA in the presence of GFP-Wtip-N, we identified SSX2IP as the candidate binding protein. SSX2IP, also known as Msd1 or ADIP, is a centriolar satellite protein that functions as a targeting factor for ciliary membrane proteins. Wtip physically associated with SSX2IP and the two proteins formed mixed spherical aggregates in overexpressing cells in a dose-dependent manner, in a process that resembles phase separation. These results suggest that the interaction between SSX2IP and Wtip is relevant to their functions at the centrosome and basal bodies. The described antibody targeting of biotin ligase should be applicable to other GFP-tagged proteins.


title: Phase-specific RNA accumulation and duplex thermodynamics in multiphase coacervate models for membraneless organelles

abstract: Liquid-liquid phase separation has emerged as an important means of intracellular RNA compartmentalization. Some membraneless organelles host two or more compartments serving different putative biochemical roles; the mechanisms for, and functional consequences of, this subcompartmentalization are not yet well understood. Here, we show that adjacent phases of decapeptide-based multiphase model membraneless organelles differ markedly in their interactions with RNA. Additionally, their coexistence introduces new equilibria that alter RNA duplex stability and RNA sorting by hybridization state. These effects require neither biospecific RNA binding sites nor full-length proteins. As such, they are general and point to more primitive versions of mechanisms operating in extant biology that could aid understanding and enable design of functional artificial membraneless organelles.


title: Engineering Gelation Kinetics in Living Silk Hydrogels by Differential Dynamic Microscopy Microrheology and Machine Learning

abstract: Microbes embedded in hydrogels comprise one form of living material. Discovering formulations that balance potentially competing mechanical and biological properties in living hydrogels--for example gel time of the hydrogel formulation and viability of the embedded organisms--can be challenging. In this work, a pipeline is developed to automate characterization of the gel time of hydrogel formulations. Using this pipeline, living materials comprised of enzymatically crosslinked silk and embedded E. coli--formulated from within a 4D parameter space--are engineered to gel within a pre-selected timeframe. Gelation time is estimated using a novel adaptation of microrheology analysis using differential dynamic microscopy (DDM). In order to expedite the discovery of gelation regime boundaries, Bayesian machine learning models are deployed with optimal decision-making under uncertainty. The rate of learning is observed to vary between AI-assisted planning and human planning, with the fastest rate occurring during AI-assisted planning following a round of human planning. For a subset of formulations gelling within a targeted timeframe of 5-15 minutes, fluorophore production within the embedded cells is substantially similar across treatments, evidencing that gel time can be tuned independent of other material properties--at least over a finite range--while maintaining biological activity.

category: bioengineering


title: Portable low-cost optical density meter

abstract:
Measuring optical density (OD) is a very common technique in biological laboratories to determine the concentration of a substance in solution or of bacteria (or microscopic particles) in suspension. For example, bacterial cultures engineered to produce (express) a protein or compound of interest are a workhorse of modern molecular biology laboratories. Commonly, the expression of the product is triggered (induced) by a chemical signal added to the culture at the proper time in the growth curve of the culture (typically in the middle of the exponential growth phase, at an OD value of [~]0.6). The most common tool for measuring OD is a spectrophotometer. However, most spectrophotometers are sophisticated, non-portable and expensive laboratory instruments, costing tens of thousands of dollars. Even a very low cost spectrophotometer for educational use costs at least US$1,000. Because of the cost, even well resourced labs have only one instrument, which becomes a bottleneck when multiple bacterial cultures need to be monitored simultaneously. The problem is more acute in developing countries, where multiple labs have to share a single spectrophotometer, or theres no such instrument at all. Having a cheap and simple device to measure OD would enable multiple people in a laboratory to monitor their bacterial cultures independently, even in resource-limited settings. At the same time, a portable OD meter could be useful for field work. Here we present the detailed build instructions and characterization of a very simple OD meter that costs only US$60, and can measure OD values from [~]0.05 to 2.0.

Specifications table

O_TBL View this table:
org.highwire.dtl.DTLVardef@721005org.highwire.dtl.DTLVardef@79c5d3org.highwire.dtl.DTLVardef@aabb95org.highwire.dtl.DTLVardef@1016f09org.highwire.dtl.DTLVardef@120f3e2_HPS_FORMAT_FIGEXP  M_TBL C_TBL


title: DENIES: A deep learning based two-layer predictor for enhancing the identification of enhancers and their strength with DNA shape information

abstract: The identification of enhancers has always been an important task in bioinformatics owing to their major role in regulating gene expression. For this reason, many computational algorithms devoted to enhancer identification have been put forward over the years. To boost the performance of their methods, more features are extracted from the single DNA sequences and integrated to develop an ensemble classifier. Nevertheless, the sequence-derived features used in previous studies can hardly provide the 3D structure information of DNA sequences, which is regarded as an important factor affecting the binding preferences of transcription factors to regulatory elements like enhancers. Given that, we here propose SENIES, a DNA shape enhanced deep learning predictor, for the identification of enhancers and their strength. The predictor consists of two layers where the first layer is for enhancer and non-enhancer identification, and the second layer is for predicting the strength of enhancers. Besides utilizing two common sequence-derived features (i.e. one-hot and k-mer) as input, it introduces DNA shape for describing the 3D structures of DNA sequences. Performance comparison with state-of-the-art methods conducted on the same datasets demonstrates the effectiveness and robustness of our method. The code implementation of our predictor is publicly available at https://github.com/hlju-liye/SENIES.

category: bioinformatics


title: SENIES: DNA Shape Enhanced Two-layer Deep Learning Predictor for the Identification of Enhancers and Their Strength


title: Ultra-rapid somatic variant detection via real-time threshold sequencing

abstract: Molecular markers are becoming increasingly important for cancer diagnosis, proper clinical trial enrollment, and even surgical decision making, motivating ultra-rapid, intraoperative variant detection. Sequencing-based detection is considered the gold standard approach, but typically takes hours to perform. In this work, we present Threshold Sequencing, a methodology for designing protocols for targeted variant detection on real-time sequencers with a minimal time to result. Threshold Sequencing analytically identifies a time-optimal threshold to stop target amplification and begin sequencing. To further reduce diagnostic time, we explore targeted Loop-mediated Isothermal Amplification (LAMP) and design a LAMP-specific bioinformatics tool--LAMPrey--to process sequenced LAMP product. LAMPreys concatemer aware alignment algorithm is designed to maximize recovery of diagnostically relevant information leading to a more rapid detection versus standard read alignment approaches. Coupled with time-optimized DNA extraction and library preparation, we demonstrate confirmation of a hot-spot mutation (250x support) from tumor tissue in less than 30 minutes.


title: riboviz 2: A flexible and robust ribosome profiling data analysis and visualization workflow

abstract:
MotivationRibosome profiling, or Ribo-seq, is the state of the art method for quantifying protein synthesis in living cells. Computational analysis of Ribo-seq data remains challenging due to the complexity of the procedure, as well as variations introduced for specific organisms or specialized analyses. Many bioinformatic pipelines have been developed, but these pipelines have key limitations in terms of functionality or usability.

ResultsWe present riboviz 2, an updated riboviz package, for the comprehensive transcript-centric analysis and visualization of Ribo-seq data. riboviz 2 includes an analysis workflow built on the Nextflow workflow management system, combining freely available software with custom code. The package is extensively documented and provides example configuration files for organisms spanning the domains of life. riboviz 2 is distinguished by clear separation of concerns between annotation and analysis: prior to a run, the user chooses a transcriptome in FASTA format, paired with annotation for the CDS locations in GFF3 format. The user is empowered to choose the relevant transcriptome for their biological question, or to run alternative analyses that address distinct questions. riboviz 2 has been extensively tested on various library preparation strategies, including multiplexed samples. riboviz 2 is flexible and uses open, documented file formats, allowing users to integrate new analyses with the pipeline.

Availabilityriboviz 2 is freely available at github.com/riboviz/riboviz.

Supplementary information


title: Compositional data analysis of microbiome and any-omics datasets: a revalidation of the additive logratio transformation

abstract: BackgroundMicrobiome and omics datasets are, by their intrinsic biological nature, of high dimensionality, characterized by counts of large numbers of components (microbial genes, operational taxonomic units, RNA transcripts, etc...). These data are generally regarded as compositional since the total number of counts identified within a sample are irrelevant. The central concept in compositional data analysis is the logratio transformation, the simplest being the additive logratios with respect to a fixed reference component. A full set of additive logratios is not isometric in the sense of reproducing the geometry of all pairwise logratios exactly, but their lack of isometry can be measured by the Procrustes correlation. The reference component can be chosen to maximize the Procrustes correlation between the additive logratio geometry and the exact logratio geometry, and for high-dimensional data there are many potential references. As a secondary criterion, minimizing the variance of the reference components log-transformed relative abundance values makes the subsequent interpretation of the logratios even easier. Finally, it is preferable that the reference component not be a rare component but well populated, and substantive biological reasons might also guide the choice if several reference candidates are identified. Results: On each of three high-dimensional datasets the additive logratio transformation was performed, using references that were identified according to the abovementioned criteria. For each dataset the compositional data structure was successfully reproduced, that is the additive logratios were very close to being isometric. The Procrustes correlations achieved for these datasets were 0.9991, 0.9977 and 0.9997, respectively. In the third case, where the objective was to distinguish between three groups of samples, the approximation was made to the restricted logratio space of the between-group variance. Conclusions: We show that for high-dimensional compositional data additive logratios can provide a valid choice as transformed variables that are (1) subcompositionally coherent, (2) explaining 100% of the total logratio variance and (3) coming measurably very close to being isometric, that is approximating almost perfectly the exact logratio geometry. The interpretation of additive logratios is simple and, when the variance of the log-transformed reference is very low, it is made even simpler since each additive logratio can be identified with a corresponding compositional component.


title: pH-dependent 11° F1FO ATP synthase sub-steps reveal insight into the FO torque generating mechanism

abstract: Most cellular ATP is made by rotary F1Fo ATP synthases using proton translocation-generated clockwise torque on the Fo c-ring rotor, while F1-ATP hydrolysis can force anticlockwise rotation and proton pumping. Although the interface of stator subunit-a containing the transmembrane half-channels and the c-ring is known from recent F1Fo structures, the torque generating mechanism remains elusive. Here, single-molecule studies reveal pH-dependent 11{degrees} rotational sub-steps in the ATP synthase direction of the E. coli c10-ring of F1Fo against the force of F1-ATPase-dependent rotation that result from H+ transfer events from Fo subunit-a groups with a low pKa to one c-subunit of the c-ring, and from an adjacent c-subunit to stator groups with a high pKa. Mutations of subunit-a residues in the proton translocation channels alter these pKa values, and the ability of synthase substeps to occur. Alternating 11{degrees} and 25{degrees} sub-steps then result in sustained ATP synthase rotation of the c10-ring.

category: biophysics


title: Lipid Bilayer Induces Contraction of the Denatured State Ensemble of a Helical-Bundle Membrane Protein

abstract:
Defining the denatured state ensemble (DSE) and intrinsically disordered proteins is essential to understanding protein folding, chaperone action, degradation, translocation and cell signaling. While a majority of studies have focused on water-soluble proteins, the DSE of membrane proteins is much less characterized. Here, we reconstituted the DSE of a helical-bundle membrane protein GlpG of Escherichia coli in native lipid bilayers and measured the DSEs conformation and compactness. The DSE was obtained using steric trapping, which couples spontaneous denaturation of a doubly biotinylated GlpG to binding of two bulky monovalent streptavidin molecules. Using limited proteolysis and mass spectrometry, we mapped the flexible regions in the DSE. Using our paramagnetic biotin derivative and double electron-electron resonance spectroscopy, we determined the dimensions of the DSE. Finally, we employed our Upside model for molecular dynamics simulations to generate the DSE including the collapsed and fully expanded states in a bilayer. We find that the DSE is highly dynamic involving the topology changes of transmembrane segments and their unfolding. The DSE is expanded relative to the native state, but only to 55-90% of the fully expanded condition. The degree of expansion depends on the chemical potential with regards to local packing and the lipid composition. Our result suggests that the E. colis native lipid bilayer promotes the association of helices in the DSE of membrane proteins and, probably in general, facilitating interhelical interactions. This tendency may be the outcome of a general lipophobic effect of proteins within the cell membranes.

SignificanceHere, we delineate the conformation of the denatured state ensemble (DSE) of a membrane protein confined in a native lipid bilayer and assay whether the bilayer permits full expansion or nonspecific collapse of the DSE. Using the intramembrane protease GlpG as a model, we find that the denatured state is a dynamic ensemble involving topological changes and local unfolding of transmembrane segments. The bilayer tends to contract the DSE relative to the fully lipid-solvated, expanded conformations while the degree of compactness is determined by the balance between protein-lipid, lipid-lipid and protein-protein interactions. These findings provide new insights into the lipid bilayer as a solvent that mediates folding, chaperone action, turnover and protein-protein interactions in cell membranes.


title: Sustained Enzymatic Activity and Flow in Crowded Protein Droplets

abstract: Living cells harvest energy from their environments to drive the chemical processes that enable life. We introduce a minimal system that operates at similar protein concentrations, metabolic densities, and length scales as living cells. This approach takes advantage of the tendency of phase-separated protein droplets to strongly partition enzymes, while presenting minimal barriers to transport of small molecules across their interface. By dispersing these microreactors in a reservoir of substrate-loaded buffer, we achieve steady states at metabolic densities that match those of the hungriest microorganisms. We further demonstrate the formation of steady pH gradients, capable of driving microscopic flows. Our approach enables the investigation of the function of diverse enzymes in environments that mimic cytoplasm, and provides a flexible platform for studying the collective behavior of matter driven far from equilibrium.


title: EPIKOL, a chromatin-focused CRISPR/Cas9-based screening platform, to identify cancer-specific epigenetic vulnerabilities

abstract: Dysregulation of the epigenome due to alterations in chromatin modifier proteins commonly contribute to malignant transformation. To discover new drug targets for more targeted and personalized therapies, functional interrogation of epigenetic modifiers is essential. We therefore generated an epigenome-wide CRISPR-Cas9 knock-out library (EPIKOL) that targets a wide-range of epigenetic modifiers and their cofactors. We conducted eight screens in two different cancer types and showed that EPIKOL performs with high efficiency in terms of sgRNA distribution, depletion of essential genes and steady behaviors of non-targeting sgRNAs. From this, we discovered novel epigenetic modifiers besides previously known ones that regulate triple-negative breast cancer and prostate cancer cell fitness. With further validation assays, we confirmed the growth-regulatory function of individual candidates, including SS18L2 and members of the NSL complex (KANSL2, KANSL3, KAT8) in triple negative breast cancer cells. Overall, we show that EPIKOL, a focused sgRNA library targeting approximately 800 genes, can reveal epigenetic modifiers that are essential for cancer cell fitness and serve as a tool to offer novel anti-cancer targets. With its thoroughly generated epigenome-wide gene list, and the relatively high number of sgRNAs per gene, EPIKOL offers a great advantage to study functional roles of epigenetic modifiers in a wide variety of research applications, such as screens on primary cells, patient-derived xenografts as well as in vivo models.

category: cancer biology


title: Cancer patient survival can be accurately parameterized, revealing time-dependent therapeutic effects and doubling the precision of small trials

abstract: Individual participant data (IPD) from completed oncology clinical trials are a valuable but rarely available source of information. A lack of minable survival distributions has made it difficult to identify factors determining the success and failure of clinical trials and improve trial design. We imputed survival IPD from [~]500 arms of phase III oncology trials (representing [~]220,000 events) and found that they are well fit by a two-parameter Weibull distribution. This makes it possible to use parametric statistics to substantially increase trial precision with small patient cohorts typical of phase I or II trials. For example, a 50-person trial parameterized using Weibull distributions is as precise as a 90-person trial evaluated using traditional statistics. Mining IPD also showed that frequent violations of the proportional hazards assumption, particularly in trials of immune checkpoint inhibitors (ICIs), arise from time-dependent therapeutic effects and hazard ratios. Thus, the duration of ICI trials has an underappreciated impact on the likelihood of their success.


title: Preparation of cationized albumin nanoparticles loaded indirubin by high pressure hemogenizer

abstract: Indirubin can be applied as an anti-cancer drug for inhibition of brain tumors. However, its performance is reduced due to hydrophobicity. In this study, we synthesized cationic human serum albumin (CHSA) nanoparticle by a new hybrid approach for improvement the surface chemistry of albumin and investigate the amount of indirubin loaded CHSA nanoparticle. In this study, the generated mechanical force from a high-pressure homogenizer (HPH) was used to make nanoparticles with a certain size with narrow polydispersity. The results indicated that the size of indirubin loaded CHSA nanoparticles were 130 nm and their zeta potential were +9. Besides, the encapsulation efficiency and drug loading capacity were found to be 85% and 5.8 %, respectively. To the best to our knowledge, this is the first time that indirubin has been used in albumin nanoparticles. In this study, indirubin loaded CHSA nanoparticles was shown can be a potential candidate for drug delivery in the treatment of glioblastoma. Moreover, the cationized form allows the chemical agent to be transmitted to the brain.


title: Dissection of N-, O- and glycosphingolipid glycosylation changes in PaTu-S pancreatic adenocarcinoma cells upon TGF-β challenge

abstract: Pancreatic ductal adenocarcinoma (PDAC) is characterized by poor prognosis and high mortality. Transforming growth factor-{beta} (TGF-{beta}) plays a key role in tumor progression, which is often associated with aberrant glycosylation. How PDAC cells respond to TGF-{beta} and the role of glycosylation therein is, however, not well known. Here, we investigated the TGF-{beta}-mediated response and glycosylation changes in SMAD4-deficient PaTu-8955S (PaTu-S) cell line. PaTu-S cells responded to TGF-{beta} by upregulating SMAD2 phosphorylation and target gene expression. TGF-{beta} induced expression of the mesenchymal marker N-cadherin, but did not significantly affect epithelial marker E-cadherin expression. The differences of N-glycans, O-glycans and glycosphingolipid (GSL) glycans in PaTu-S cells with TGF-{beta} stimulation were examined. TGF-{beta} treatment primarily induced N-glycome aberrations involving elevated levels of branching, core fucosylation, and sialylation in PaTu-S cells, in line with TGF-{beta}-induced changes in the expression of glycosylation-related genes. In addition, we observed differences in O- and GSL-glycosylation profiles after TGF-{beta} treatment, including lower levels of sialylated Tn antigen, and neoexpression of globosides. Furthermore, SOX4 expression was upregulated upon TGF-{beta} stimulation, and its depletion blocked the TGF-{beta}-induced N-glycomic changes. Thus, our study provides a mechanism by which TGF-{beta}-induced N-glycosylation changes in SOX4 dependent and SMAD4 independent manner in pancreatic cancer cells. Our results open up avenues to study the relevance of glycosylation in TGF-{beta} signaling in SMAD4 inactivated PDAC.


title: Molecular dynamics simulations of zfP2X4 receptors

abstract: The P2X4 receptor plays a prominent role in cellular responses to extracellular ATP. Through classical all-atom molecular dynamics (MD) simulations totaling 24 {micro}s we have investigated how metal-complexed ATP stabilizes the channels open state and prevents its closing. We have identified two metal-binding sites, magnesium (Mg2+) and potassium (K+), one at the intersection of the three subunits in the ectodomain (MBS1) and the second one near the ATP binding site (MBS2), similar to those characterized in Gulf coast P2X. Our data indicate that when Mg2+ and K+ ions are complexed with ATP, the channel is locked into an open state. Interestingly, irrespective of the number of bound ATP molecules, Mg2+ ions bound to the MBS2 resisted collapsing of the open state protein to a closed state by stabilizing the ATP-protein interactions. However, when Mg2+ in the MBS2 was replaced with K+ ions, as might be expected when in equilibrium with an extracellular solution, the interactions between the subunits were weakened and we found evidence of pore collapse. This collapse was apparent when fewer than two ATP were bound to MBS2 in the presence of K+. Therefore, the different capacities of common cations to stabilize the channel may underlie a mechanism governing P2X4 channel gating in physiological systems. This study provides structural insights into the differential modulation of ATP activation of P2X4 by Mg2+ and K+.

category: physiology


title: Modulation of P2X4 pore closure by magnesium,potassium, and ATP


title: The bitter end: T2R bitter receptor agonists elevate nuclear calcium and induce apoptosis in non-ciliated airway epithelial cells

abstract: Bitter taste receptors (T2Rs) localize to airway motile cilia and initiate innate immune responses in retaliation to bacterial quorum sensing molecules (acyl-homoserine lactones and quinolones). Activation of T2Rs leads to calcium-driven NO production that increases cilia beating and directly kills bacteria. Several airway diseases, including chronic rhinosinusitis, COPD, and cystic fibrosis, are characterized by epithelial remodeling, including loss of motile cilia and/or squamous metaplasia. To understand the function of T2Rs within the altered landscape of airway disease, we studied T2Rs in non-ciliated airway cell lines and primary cells de-differentiated to a squamous phenotype. In differentiated cells, T2Rs localize to cilia, however in de-differentiated, non-ciliated cells they localize to the nucleus. Cilia and nuclear import utilize many shared proteins, thus in the absence of motile cilia some T2Rs may target to the nucleus. T2R agonists selectively elevated both nuclear and mitochondrial calcium through a G-protein-coupled receptor, phospholipase C, and InsP3 receptor-dependent mechanism. Additionally, T2R agonists decreased nuclear cAMP, increased nitric oxide, and increased cGMP, consistent with T2R signaling. Furthermore, exposure to T2R agonists led to nuclear calcium-induced mitochondrial depolarization and caspase activation. T2R agonists induced apoptosis in primary bronchial and nasal cells differentiated at air-liquid interface but then induced to a squamous phenotype by apical submersion. Air-exposed well-differentiated cells did not die. This T2R-induced apoptosis may be a last-resort defense against infection, possibly when bacteria have breached the epithelial barrier and reach non-ciliated cells below. However, it may also increase susceptibility of de-differentiated or remodeled epithelia to damage by bacterial metabolites. Moreover, the T2R-activated apoptosis pathway occurs in airway cancer cells. T2Rs may thus contribute to microbiome-tumor cell crosstalk in airway cancers. T2R agonists may also be useful topical therapeutics (e.g., delivered by nasal rinse or nebulizer) for activating airway cancer cell apoptosis without killing surrounding differentiated tissue.


title: The race goes on: A fall armyworm-resistant maize inbred line influences insect oral secretion elicitation activity and nullifies herbivore suppression of plant defense

abstract:
O_LIFall armyworm (Spodoptera frugiperda) is an invasive lepidopteran pest with strong feeding preference towards maize (Zea mays). Its success on maize is facilitated by a suite of specialized detoxification and manipulation mechanisms that curtail host plant defense responses.
C_LIO_LIIn this study, we identified a Chinese maize inbred line Xi502 that was able to mount effective defense in response to fall armyworm attack. Comparative transcriptomics analyses, phytohormonal measurements, and targeted benzoxazinoid quantification consistently demonstrate significant inducible defense responses in Xi502, but not in the susceptible reference inbred line B73.
C_LIO_LIIn 24 hours, fall armyworm larvae feeding on B73 showed accelerated maturation-oriented transcriptomic responses and more changes in detoxification gene expression compared to their Xi502-fed sibling. Interestingly, oral secretions collected from larvae fed on B73 and Xi502 leaves demonstrated distinct elicitation activity when applied on either host genotypes, suggesting that variation in both insect oral secretion composition and host plant alleles could influence plant defense response.
C_LIO_LIThese results revealed host plant adaptation towards counter-defense mechanisms in a specialist insect herbivore, adding yet another layer to the evolutionary arms race between maize and fall armyworm. This could facilitate future investigation into the molecular mechanisms in this globally important crop-pest interaction system.
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category: plant biology


title: Lukea gen. nov. (Monodoreae-Annonaceae) with two new species of shrub from the forests of the Udzungwas, Tanzania & Kaya Ribe, Kenya.

abstract:
A new genus, Lukea Gosline & Cheek (Annonaceae), is erected for two new species to science, Lukea quentinii Cheek & Gosline from Kaya Ribe, S.E. Kenya, and Lukea triciae Cheek & Gosline from the Udzungwa Mts, Tanzania. Lukea is characterised by a flattened circular bowl-shaped receptacle-calyx with a corolla of three petals that give the buds and flowers a unique appearance in African Annonaceae. Both species are extremely rare shrubs of small surviving areas of lowland evergreen forest under threat of habitat degradation and destruction and are provisionally assessed as Critically Endangered and Endangered respectively using the IUCN 2012 standard. Both species are illustrated and mapped. Material of the two species had formerly been considered to be possibly Uvariopsis Engl. & Diels, and the genus Lukea is placed in the Uvariopsis clade of the Monodoreae (consisting of the African genera Uvariodendron (Engl. & Diels) R.E.Fries, Uvariopsis, Mischogyne Exell, Dennettia Bak.f., and Monocyclanthus Keay).

The clade is characterised by often conspicuous, finely reticulate quaternary nervation and incomplete or absent connective shields (in Annonaceae the connective shield is usually complete). Morphologically Lukea is distinct for its broad, turbinate, fleshy pedicel, a synapomorphy. It appears closest to the West African monotypic Monocyclanthus, sharing a trait unusual in the Annonaceae: the calyx in both genera forms a shallow bowl (calyx lobes are absent or vestigial), barely enclosing the base of the petals at anthesis, and persisting as a living, leathery disc at least until the fruit is mature. The placement of Lukea within the Uvariopsis clade is discussed.


title: Herpetologists' Conservation Research Focus Drives Their Intentions to Participate in Future Public Engagement

abstract:
Public Engagement with Science (PES) is a popular topic in the science community due to general concerns about public support for science, attitudes toward science, and changes in scientific funding requirements. PES may be especially relevant in conservation disciplines as the public plays an important role in conservation practice. Herpetofauna specifically stand to benefit, as PES activities can help improve attitudes and conservation behavior of participants toward uncharismatic species. We assessed the current scope of herpetologists PES activities and investigated factors associated with their participation in PES. We used a closed-ended question survey distributed via the listservs of four American herpetological organizations. Herpetologists intentions to engage at least 10 hours in the next 12 months significantly differed between herpetologists with high and low conservation research focuses, but hours of engagement in the past 12 months was not significantly different among these groups. Despite most responding herpetologists having limited formal training, time, resources, and institutional support, many participated in a variety of PES activities, often utilizing partnerships and their own resources. Sampled herpetologists rarely evaluated their PES activities or considered publishing about their engagement activities. Some respondents expressed unease with the idea of message framing. Respondents were interested in evaluation training and providing accessible opportunities, and grant funds were the most likely interventions to increase herpetologists participation in PES. These results provide reference data and insight into the public engagement practices and needs of practicing herpetologists and conservation scientists.

Author statementWe informed participants of their rights and protections as approved by University of Florida IRB201800258. None of the authors have conflicts of interest related to this research. Funding for the research was provided by a Roger Conant Grant from the Society for the Study of Amphibians and Reptiles (SSAR). SSAR had no role in interpretation of data, the writing of the report, or the decision to submit the article for publication.

category: scientific communication and education


title: Navigating Multi-scale Cancer Systems Biology towards Model-driven Personalized Therapeutics

abstract: Rapid advancements in high-throughput omics technologies and experimental protocols have led to the generation of vast amounts of biomolecular data on cancer that now populates several online databases and resources. Cancer systems biology models built on top of this data have the potential to provide specific insights into complex multifactorial aberrations underpinning tumor initiation, development, and metastasis. Furthermore, the annotation of these single- or multi-scale models with patient data can additionally assist in designing personalized therapeutic interventions as well as aid in clinical decision-making. Here, we have systematically reviewed the emergence and evolution of (i) repositories with scale-specific and multiscale biomolecular cancer data, (ii) systems biology models developed using this data, (iii) associated simulation software for development of personalized cancer therapeutics, and (iv) translational attempts to pipeline multi-scale panomics data for data-driven in silico clinical oncology. The review concludes by highlighting that the absence of a generic, zero-code, panomics-based multi-scale modeling pipeline and associated software framework, impedes the development and seamless deployment of personalized in silico multi-scale models in clinical settings.

category: systems biology


title: The mechanism of artemisinin resistance of Plasmodium falciparum malaria parasites originates in their initial transcriptional response.

abstract:
The emergence and spread of artemisinin resistant Plasmodium falciparum, first in the Greater Mekong Subregion (GMS), and now in East Africa, is a major threat to global malaria eliminations ambitions. To investigate the artemisinin resistance mechanism, transcriptome analysis was conducted of 577 P. falciparum isolates collected in the GMS between 2016-2018. A specific artemisinin resistance-associated transcriptional profile was identified that involves a broad but discrete set of biological functions related to proteotoxic stress, host cytoplasm remodeling and REDOX metabolism. The artemisinin resistance-associated transcriptional profile evolved from initial transcriptional responses of susceptible parasites to artemisinin. The genetic basis for this adapted response is likely to be complex.

One sentence summaryThe transcriptional profile that characterize artemisinin resistant infections with malaria parasites Plasmodium falciparum originates in the initial transcriptional response to the drug.


title: Metabolic Dynamics in Escherichia coli-based Cell-Free Systems

abstract:
The field of metabolic engineering has yielded remarkable accomplishments in using cells to produce valuable molecules, and cell-free expression (CFE) systems have the potential to push the field even further. However, CFE systems still face some outstanding challenges, including endogenous metabolic activity that is poorly understood yet has a significant impact on CFE productivity. Here, we use metabolomics to characterize the temporal metabolic changes in CFE systems and their constituent components, including significant metabolic activity in central carbon and amino acid metabolism. We find that while changing the reaction starting state via lysate pre-incubation impacts protein production, it has a comparatively small impact on metabolic state. We also demonstrate that changes to lysate preparation have a larger effect on protein yield and temporal metabolic profiles, though general metabolic trends are conserved. Finally, while we improve protein production through targeted supplementation of metabolic enzymes, we show that the endogenous metabolic activity is fairly resilient to these enzymatic perturbations. Overall, this work highlights the robust nature of CFE reaction metabolism as well as the importance of understanding the complex interdependence of metabolites and proteins in CFE systems to guide optimization efforts.

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title: Ranking Reprogramming Factors for Directed Differentiation

abstract: Transcription factor over-expression is a proven method for reprogramming cells to a desired cell type for regenerative medicine and therapeutic discovery. However, a general method for the identification of reprogramming factors to create an arbitrary cell type is an open problem. We examine the success rate of methods and data for directed differentiation by testing the ability of nine computational methods (CellNet, GarNet, EBSeq, AME, DREME, HOMER, KMAC, diffTF, and DeepAccess) to correctly discover and rank candidate factors for eight target cell types with known reprogramming solutions. We compare methods that utilize gene expression, biological networks, and chromatin accessibility data to identify eight sets of known reprogramming factors and comprehensively test parameter and pre-processing of input data to optimize performance of these methods. We find the best factor identification methods can identify an average of 50-60% of reprogramming factors within the top 10 candidates, and methods that use chromatin accessibility perform the best. Among the chromatin accessibility methods, complex methods DeepAccess and diffTF are more likely to consistently correctly rank the significance of transcription factor candidates within reprogramming protocols for differentiation. We provide evidence that AME and DeepAccess are optimal methods for transcription factor recovery and ranking which will allow for systematic prioritization of transcription factor candidates to aid in the design of novel reprogramming protocols.


title: A toolbox for efficient proximity-dependent biotinylation in zebrafish embryos

abstract: Understanding how proteins are organized in compartments is essential to elucidating their function. While proximity-dependent approaches such as BioID have enabled a massive increase in information about organelles, protein complexes and other structures in cell culture, to date there have been only a few studies in living vertebrates. Here, we adapted proximity labeling for protein discovery in vivo in the vertebrate model organism, zebrafish. Using lamin A (LMNA) as bait and green fluorescent protein (GFP) as a negative control, we developed, optimized, and benchmarked in vivo TurboID and miniTurbo labeling in early zebrafish embryos. We developed both an mRNA injection protocol and a transgenic system in which transgene expression is controlled by a heat shock promoter. In both cases, biotin is provided directly in the egg water, and we demonstrate that 12 hours of labeling are sufficient for biotinylation of prey proteins, which should permit time-resolved analysis of development. After statistical scoring, we found that the proximal partners of LMNA detected in each system were enriched for nuclear envelope and nuclear membrane proteins, and included many orthologs of human proteins identified as proximity partners of lamin A in mammalian cell culture. The tools and protocols developed here will allow zebrafish researchers to complement genetic tools with powerful proteomics approaches.


title: The Age-Dependent Decline in Neuron Growth Potential in the CNS is Associated with an Age-Related Dysfunction of Neuronal Mitochondria

abstract: The age of incidence of Spinal Cord Injury (SCI) and the average age of people living with SCI is continuously increasing. In contrast, SCI is extensively modelled in young adult animals, hampering translation of research to clinical application. While there has been significant progress in manipulating axon growth after injury, how it is impacted by aging impacts this is still unknown. Aging is associated with a decline in mitochondrial functions, whereas mitochondria are essential to successful neurite and axon growth. Using isolation and culture of adult cortical neurons, we have analyzed mitochondrial changes in 2-, 6-, 12- and 18-month mice. We observed reduced neurite growth in older neurons. Older neurons also showed dysfunctional respiration, reduced membrane potential, and altered mitochondrial membrane transport proteins; however mitochondrial DNA (mtDNA) abundance and cellular ATP were increased. Taken together, these data suggest dysfunctional mitochondria in older neurons are involved in the age-dependent reduction in neuron growth. Both normal aging and traumatic injury are associated with mitochondrial dysfunction, posing a challenge for an aging SCI population as the two elements can compound one another to worsen injury outcomes. The results of this study highlight this as an area of great interest in CNS trauma.

category: neuroscience


title: Early Detection of Tau Pathology

abstract:
While a definitive Alzheimers disease (AD) diagnosis remains a post-mortem exercise, the ATN Research Framework proposed by the National Institute on Aging and the Alzheimers Association utilizes a score representing the presence of amyloid deposits (A), tau deposits (T) and neuronal degeneration markers (N), with A+T+ necessary for a positive diagnosis. Current detection of tau pathology lags amyloid detection by years and by the time both markers are detected the disease is fairly advanced. We describe the development of a new generation of molecular imaging probes for in vivo detection of cells undergoing abnormal phosphorylation representing the initial stages of pTau pathology, potentially enabling a very early stage diagnosis of AD. We describe a novel nanoparticle formulation that binds such abnormally phosphorylating cells in a mouse model of tau pathology, enabling in vivo visualization of the hyperphosphorylative state by magnetic resonance imaging. Our results demonstrate the potential of this novel platform to identify a correlative marker signifying the development of future tau pathology, and has implications for early-stage diagnosis of Alzheimers disease.

Graphical Abstract

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Hyperphosphorylative conditions provoke neuronal cells to undergo changes including on the cell surface. Translocation of Vimentin to the cell surface was exploited to generate an aptamer that was developed for in vivo use as targeted liposomal nanoparticle TauX for early MRI detection of tau pathology in a mouse model

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title: Pre-training RNNs on ecologically relevant tasks explains sub-optimal behavioral reset

abstract: The strategies found by animals facing a new task are determined both by individual experience and by structural priors evolved to leverage the statistics of natural environments. Rats can quickly learn to capitalize on the trial sequence correlations of two-alternative forced choice (2AFC) tasks after correct trials, but consistently deviate from optimal behavior after error trials, when they waive the accumulated evidence. To understand this outcome-dependent gating, we first show that Recurrent Neural Networks (RNNs) trained in the same 2AFC task outperform rats as they can readily learn to use across-trial information both after correct and error trials. We hypothesize that, while RNNs can optimize their behavior in the 2AFC task without any a priori restrictions, rats strategy is constrained by a structural prior adapted to a natural environment in which rewarded and non-rewarded actions provide largely asymmetric information. When pre-training RNNs in a more ecological task with more than two possible choices, networks develop a strategy by which they gate off the across-trial evidence after errors, mimicking rats behavior. Population analyses show that the pre-trained networks form an accurate representation of the sequence statistics independently of the outcome in the previous trial. After error trials, gating is implemented by a change in the network dynamics which temporarily decouples the categorization of the stimulus from the across-trial accumulated evidence. Our results suggest that the suboptimal behavior observed in rats reflects the influence of a structural prior that reacts to errors by isolating the network decision dynamics from the context, ultimately constraining the performance in a 2AFC laboratory task.


title: Ecologically pre-trained RNNs explain suboptimal animal decisions


title: Neuro-musculoskeletal Upper Limb in-silico asvirtual patient

abstract: Virtual patients and physiologies allow experimentation, design, and early-stage clinical trials in-silico. Virtual patient technology for human movement systems that encompasses musculoskeleton and its neural control are few and far in between. In this work, we present one such neuro-musculoskeletal upper limb in-silico model. This upper limb is both modular in architecture and generates movement as an emergent phenomenon out of a multiscale co-simulation of spinal cord neural control and musculoskeletal dynamics. It is developed on the NEUROiD movement simulation platform that enables a co-simulation of popular neural simulator NEURON and the musculoskeletal simulator OpenSim. In this work, we describe the design and development of the upper limb in a modular fashion, while reusing existing models and modules. We further characterize and demonstrate the use of this model in generating a range of commonly observed movements by means of a spatio temporal stimulation pattern delivered to the cervical spinal cord. We believe this work enables a first and small step towards an in-silico paradigms for understanding upper limb movement, disease pathology, medication, and rehabilitation.


title: Differential sphingosine-1-phosphate receptor-1 (S1PR1) protein expressions in the dorsolateral prefrontal cortex between schizophrenia Type 1 and Type 2

abstract: Understanding the etiology and treatment approaches in schizophrenia is challenged in part by the heterogeneity of this disorder. One encouraging progress is the growing evidence that there are subtypes of schizophrenia that may relate to disease duration and premorbid severity. Recent in vitro findings of messenger ribonucleic acid (mRNA) gene expression on postmortem dorsolateral prefrontal cortex (DLPFC) showed that schizophrenia has two subtypes, those with a relatively normal DLPFC transcriptome (Type 1) and those with differentially expressed genes (Type 2). Sphingosine-1-phosphate receptor-1 (S1PR1) is one of the genes that was highly upregulated in Type 2 compared to Type 1 and controls. The impact of that finding is limited because it only can be confirmed through analysis of autopsy tissue, and the clinical characteristics such as symptoms severity or illness duration was not available from that Medical Examiner based autopsy study. However, S1PR1 has great potential because it is a target gene that can be accessed via positron emission tomography (PET) in vivo using specific radioligands (starting with [11C]CS1P1) successfully developed at our center in human brain imaging. As a preliminary study to validate this PET target in schizophrenia, S1PR1 protein expression was assessed by receptor autoradiography (ARG) using [3H]CS1P1 and immunohistochemistry (IHC) in the DLPFC from patients with schizophrenia classified as Type 1 or Type 2 based on their DLPFC transcriptomes and from controls. Our analyses demonstrate that ARG S1PR1 protein expression is significantly higher in Type 2 compared to Type 1 (p < 0.05) and controls (p < 0.05), which was consistent with previous mRNA S1PR1. These findings support the possibility that PET S1PR1 can be used as a future imaging biomarker to distinguish these subgroups of schizophrenic patients during life with obvious implications for both patient management and the design of clinical trials to validate novel pharmacologic therapies.


title: Differential sphingosine-1-phosphate receptor-1 protein expression in the dorsolateral prefrontal cortex between schizophrenia Type 1 and Type 2


title: Sequence and functional characterization of a public HIV-specific antibody clonotype

abstract: Public antibody clonotypes shared among multiple individuals have been identified for several pathogens. However, little is known about the limits of what constitutes a public clonotype. Here, we characterize the sequence and functional properties of antibodies from a public HIV-specific clonotype comprising sequences from 3 individuals. Our results showed that antigen specificity for the public antibodies was modulated by the VH, but not VL, germline gene. Non-native pairing of public heavy and light chains from different donors resulted in antibodies with consistent antigen specificity, suggesting functional complementation of sequences within the public antibody clonotype. The strength of antigen recognition appeared to be dependent on the specific antibody light chain used, but not on other sequence features such as germline or native-antibody sequence identity. Understanding the determinants of antibody clonotype "publicness" can provide insights into the fundamental rules of host-pathogen interactions at the population level, with implications for clonotype-specific vaccine development.

category: immunology


title: Disrupting the CD177:proteinase 3 membrane complex reduces anti-PR3 antibody-induced neutrophil activation

abstract: CD177 is a neutrophil-specific receptor presenting proteinase 3 (PR3) autoantigen on the neutrophil surface. CD177 expression is restricted to a neutrophil subset resulting in CD177pos/mPR3high and CD177neg/mPR3low populations. The size of the CD177pos/mPR3high subset has implications for anti-neutrophil cytoplasmic autoantibody (ANCA)-associated autoimmune vasculitis (AAV) where patients harbor PR3-specific ANCA that activate neutrophils. We generated high affinity anti-CD177 monoclonal antibodies, some of which interfered with PR3 binding to CD177 (PR3 "blockers") as determined by surface plasmon resonance spectroscopy, and used them to test the effect of competing PR3 from the surface of CD177pos neutrophils. Because intact anti-CD177 antibodies also caused neutrophil activation, we prepared non-activating Fab fragments of a PR3 blocker and non-blocker that bound specifically to CD177pos neutrophils by flow cytometry. We observed that Fab blocker clone 40, but not non-blocker clone 80, dose-dependently reduced anti-PR3 antibody binding to CD177pos neutrophils. Importantly, preincubation with clone 40 significantly reduced respiratory burst in primed neutrophils challenged either with monoclonal antibodies to PR3 or PR3-ANCA IgG from AAV patients. After separating the two CD177/mPR3 neutrophil subsets from individual donors by magnetic sorting, we found that PR3-ANCA provoked significantly more superoxide production in CD177pos/mPR3high than in CD177neg/mPR3low neutrophils, and that anti-CD177 Fab clone 40 reduced the superoxide production of CD177pos cells to the level of the CD177neg cells. Our data demonstrate the importance of the CD177:PR3 membrane complex in maintaining a high ANCA epitope density and thereby underscore the contribution of CD177 to the severity of PR3-ANCA diseases.


title: Genomic Mining and Physiological Characterization of new Halophilic Plant Growth Promoting Bacilli

abstract: Massive application of chemical fertilizers and pesticides has been the main strategy used to cope with the rising crop demands in the last decades. The indiscriminate use of chemicals while providing a temporary solution to food demand has led to a decrease in crop productivity and an increase in the environmental impact of modern agriculture. A sustainable alternative to the use of chemicals for crop production is the use of microorganisms naturally capable of enhancing plant growth and protecting crops from pests, known as Plant-Growth-Promoting Bacteria (PGPB). Aim of the present study was to isolate and characterize PGPB from salt-pans sand samples able to ameliorate plant fitness. To survive high salinity, salt-tolerant microbes produce a broad range of compounds with heterogeneous biological activities that are potentially beneficial for plant growth. We have isolated and screened in vitro a total of 20 halophilic spore-forming bacteria for phyto-beneficial traits and compared the results with two Bacilli recently isolated from the rhizosphere of the same collection site and recently characterized as potential biocontrol agents. Whole-genome analysis on five selected halophilic strains confirmed the presence of numerous gene clusters with PGP and biocontrol functions and of novel secondary-metabolite biosynthetic genes potentially involved in plant growth promotion and protection. The predicted biocontrol potential was confirmed in dual culture assays against several phytopathogenic fungi and bacteria. Interestingly, the absence of predicted gene clusters with known biocontrol functions in some of the isolates was not predictive of the in vitro results, supporting the need of combining laboratory assays and genome mining in PGPB identification for future applications.

category: microbiology


title: The Campylobacter jejuni CadF and FlpA fibronectin binding proteins facilitate signaling via host cell focal adhesions to inhibit cell motility and impede wound repair

abstract: Campylobacter jejuni is a major foodborne pathogen that exploits the focal adhesions of intestinal cells to promote invasion and cause severe gastritis. Focal adhesions are multiprotein complexes involved in bidirectional signaling between the actin cytoskeleton and the extracellular matrix. We investigated the dynamics of focal adhesion structure and function in C. jejuni infected cells using a comprehensive set of approaches, including confocal microscopy of live and fixed cells, immunoblots, and super-resolution iPALM. We found that C. jejuni infection of epithelial cells results in an increased focal adhesion size and altered topology. These changes resulted in a persistent modulatory effect on the host cell focal adhesion, as evidenced by an increase in cell adhesion strength, a decrease in individual cell motility, and a reduction of collective cell migration. We discovered that C. jejuni infection causes an increase in phosphorylation of paxillin and an alteration of paxillin turnover at the focal adhesion, which together represent a potential mechanistic basis for altered cell motility. Finally, we observed that infection of epithelial cells with the C. jejuni wild-type strain in the presence of protein synthesis inhibitor, a C. jejuni CadF and FlpA fibronectin-binding protein mutant, or a C. jejuni flagellar export mutant blunts paxillin phosphorylation and partially re-establishes individual host cell motility and collective cell migration. These findings provide a potential mechanism for the restricted intestinal repair observed in C. jejuni-infected animals and raise the possibility that bacteria targeting extracellular matrix components can alter cell behavior after binding and internalization by manipulating focal adhesions.


title: Campylobacter jejuni trigger signaling through host cell focal adhesions to inhibit cell motility and impede wound repair


title: Interplay between cell proliferation and recruitment controls the duration of growth and final size of the Drosophila wing

abstract:
How organs robustly attain a final size despite perturbations in cell growth and proliferation rates is a fundamental question in developmental biology. Since organ growth is an exponential process driven mainly by cell proliferation, even small variations in cell proliferation rates, when integrated over a relatively long time, will lead to large differences in size, unless intrinsic control mechanisms compensate for these variations. Here we use a mathematical model to consider the hypothesis that in the developing wing of Drosophila, cell recruitment, a process in which undifferentiated neighboring cells are incorporated into the wing primordium, determines the time in which growth is arrested in this system. Under this assumption, our model shows that perturbations in proliferation rates of wing-committed cells are compensated by an inversely proportional duration of growth. This mechanism ensures that the final size of the wing is robust in a range of cell proliferation rates. Furthermore, we predict that growth control is lost when fluctuations in cell proliferation affects both wing-committed and recruitable cells. Our model suggests that cell recruitment may act as a temporal controller of growth to buffer fluctuations in cell proliferation rates, offering a solution to a long-standing problem in the field.

Graphical abstract

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category: developmental biology


title: Loss of imprinting of the Igf2-H19 ICR1 enhances placental endocrine capacity via sex-specific alterations in signalling pathways in the mouse.

abstract:
Imprinting control region (ICR1) controls the expression of the Igf2 and H19 genes in a parent-of-origin specific manner. Appropriate expression of the Igf2-H19 locus is fundamental for normal fetal development, yet the importance of ICR1 in the placental production of hormones that promote maternal nutrient allocation to the fetus is unknown. To address this, we used a novel mouse model to selectively delete ICR1 in the endocrine junctional zone (Jz) of the mouse placenta (Jz-{Delta}ICR1). The Jz-{Delta}ICR1 mice exhibit increased Igf2 and decreased H19 expression specifically in the Jz. This was accompanied by an expansion of Jz endocrine cell types due to enhanced rates of proliferation and increased expression of pregnancy-specific glycoprotein 23 in the placenta of both fetal sexes. However, changes in the endocrine phenotype of the placenta were related sexually-dimorphic alterations to the abundance of IGF2 receptors and downstream signalling pathways (PI3K-AKT and MAPK). There was no effect of Jz-{Delta}ICR1 on the expression of targets of the H19 embedded miR-675 or on fetal weight. Our results demonstrate that ICR1 controls placental endocrine capacity via sex-dependant changes in signalling.

Summary statementImprinting at Igf2-H19 ICR1 regulates endocrine cell formation and function via sexually-dimorphic changes in PI3K-AKT and MAPK signalling in the mouse.


title: Assessing the ubiquity and origins of structural maintenance of chromosomes (SMC) proteins in eukaryotes

abstract: Structural maintenance of chromosomes (SMC) protein complexes are common in Bacteria, Archaea, and Eukaryota. SMC proteins, together with the proteins related to SMC (SMC-related proteins), constitute a superfamily of ATPases. Bacteria/Archaea and Eukaryotes are distinctive from one another in terms of the repertory of SMC proteins. A single type of SMC protein is dimerized in the bacterial and archaeal complexes, whereas eukaryotes possess six distinct SMC subfamilies (SMC1-6), constituting three heterodimeric complexes, namely cohesin, condensin, and SMC5/6 complex. Thus, to bridge the homodimeric SMC complexes in Bacteria and Archaea to the heterodimeric SMC complexes in Eukaryota, we need to invoke multiple duplications of an SMC gene followed by functional divergence. However, to our knowledge, the evolution of the SMC proteins in Eukaryota had not been examined for more than a decade. In this study, we reexamined the ubiquity of SMC1-6 in phylogenetically diverse eukaryotes that cover the major eukaryotic taxonomic groups recognized to date and provide two novel insights into the SMC evolution in eukaryotes. First, multiple secondary losses of SMC5 and SMC6 occurred in the eukaryotic evolution. Second, the SMC proteins constituting cohesin and condensin (i.e., SMC1-4), and SMC5 and SMC6 were derived from closely related but distinct ancestral proteins. Based on the above-mentioned findings, we discuss how SMC1-6 have diverged from the archaeal homologs.


title: Ubiquity and origins of structural maintenance of chromosomes (SMC) proteins in eukaryotes


title: Kernel Local Fisher Discriminant Analysis of Principal Components (KLFDAPC) significantly improves the accuracy of predicting geographic origin of individuals

abstract: Geographic patterns of human genetic variation provide important insights into human evolution and disease. A commonly used tool to detect geographic patterns from genetic data is principal components analysis (PCA) or the supervised linear discriminant analysis of principal components (DAPC). However, genetic features produced from both approaches could fail to correctly characterize population structure for complex scenarios involving admixture. In this study, we introduce Kernel Local Fisher Discriminant Analysis of Principal Components (KLFDAPC), a supervised nonlinear approach for inferring individual geographic genetic structure that could rectify the limitations of these approaches by preserving the multimodal space of samples. We tested the power of KLFDAPC to infer population structure and to predict individual geographic origin using neural networks. Simulation results showed that KLFDAPC significantly improved the population separability compared with PCA and DAPC. The application to POPRES and CONVERGE datasets indicated that the first two reduced features of KLFDAPC correctly recapitulated the geography of individuals, and significantly improved the accuracy of predicting individual geographic origin when compared to PCA and DAPC. Therefore, KLFDAPC can be useful for geographic ancestry inference, design of genome scans and correction for spatial stratification in GWAS that link genes to adaptation or disease susceptibility.


title: Chromatin accessibility of primary human cancers ties regional mutational processes with tissues of origin

abstract:
BackgroundRegional distribution of somatic mutations in cancer genomes associates with DNA replication timing (RT) and chromatin accessibility (CA), however normal tissues and cell lines have contributed these insights while associations with the epigenomes of primary cancers remain uncharacterized.

ResultsHere we model megabase-scale mutation burden in whole cancer genomes using [~]900 CA and RT profiles of primary cancers, normal tissues, and cell lines. CA profiles of primary cancers, rather than normal tissues, predict regional mutagenesis in most cancer types. Regional mutation burden associates with the CA profiles of matching cancer types, indicating tissue-specific determinants of mutagenesis. However, mutagenesis in squamous cell and lymphoid cancers instead associates with RT profiles. Mutational signatures also show tissue-specific associations with cancer epigenomes, especially for carcinogen-induced and unannotated signatures. Lastly, while each cancer type includes certain frequently-mutated genomic regions exceeding epigenome-informed predictions of mutation burden, these regions show a pan-cancer convergence to biological processes involved in development and cancer. Thus, modelling excess mutations using epigenomes highlights known cancer driver genes as well as frequently mutated non-coding regions.

ConclusionsThe dominant association of regional mutation burden with cancer epigenomes suggests that many passenger mutations are determined by the epigenetic landscapes of transformed cells and may occur later in tumor evolution. CA-informed models help find cancer genes and pathways with positive selection and highlight regions where additional mutation burden is contributed by local mutational processes. This study underlines the complex interplay of mutational processes, genome function and evolution in cancer and tissues of origin.


title: Mutational signatures of complex genomic rearrangements in human cancer

abstract: Complex genomic rearrangements (CGRs) are common in cancer and are known to form via two aberrant cellular structures--micronuclei and chromatin bridge. However, which mechanism is more relevant to CGR formation in cancer cells and whether there are other undiscovered mechanisms remain open questions. Here, we analyze 2,014 CGRs from 2,428 whole-genome sequenced tumors and deconvolute six CGR signatures based on the topology of CGRs. Through rigorous benchmarking, we show that our CGR signatures are highly accurate and biologically meaningful. Three signatures can be attributed to known biological processes--micronuclei- and chromatin-bridge-induced chromothripsis and extrachromosomal DNA. More than half of the CGRs belong to the remaining three newly discovered signatures. A unique signature (we named "hourglass chromothripsis") with highly localized breakpoints and small amount of DNA loss is abundant in prostate cancer. Through genetic association analysis, we find SPOP as a candidate gene causing hourglass chromothripsis and playing important role in maintaining genome integrity. Our study offers valuable insights into the formation of CGRs.


title: TAPIOCA: Topological Attention and Predictive Inference of Chromatin Arrangement Using Epigenetic Features

abstract:
Chromatin conformation is an important characteristic of the genome which has been repeatedly demonstrated to play vital roles in many biological processes. Chromatin can be characterized by the presence or absence of structural motifs called topologically associated domains. The de facto strategy for determination of topologically associated domains within a cell line is the use of Hi-C sequencing data. However Hi-C sequencing data can be expensive or otherwise unavailable. Various epigenetic features have been hypothesized to contribute to the determination of chromatin conformation. Here we present TAPIOCA, a self-attention based deep learning transformer algorithm for the prediction of chromatin topology which circumvents the need for labeled Hi-C data and makes effective predictions of chromatin conformation organization using only epigenetic features. TAPIOCA outperforms prior art in established metrics of TAD prediction, while generalizing across cell lines beyond those used in training.

Availabilitythe source code of TAPIOCA and training and test datasets are available at https://github.com/Max-Highsmith/TAPIOCA

Author SummaryIn this paper we outline a machine learning approach for predicting the topological organization of chromosomes using epigenetic track data as features. By utilizing an architecture inspired by the sequence transduction transformer network we are able to effectively predict multiple metrics used to characterize topologically associated domains. Our experimental results demonstrate that once trained our algorithm can effectively predict topological organization on novel cell lines all without any exposure to original Hi-C data in test datasets.


title: Selective G protein signaling driven by Substance P-Neurokinin Receptor structural dynamics

abstract: The neuropeptide Substance P (SP) is important in pain and inflammation. SP activates the neurokinin-1 receptor (NK1R) to signal via Gqand Gs proteins. Neurokinin A also activates NK1R, but leads to selective Gq signaling. How two stimuli yield distinct G-protein signaling at the same G-protein-coupled-receptor remains unclear. We determined cryo-EM structures of active NK1R bound to SP or the Gq-biased peptide SP6-11. Peptide interactions deep within NK1R are critical for receptor activation. Conversely, interactions between SP and NK1R extracellular loops are required for potent Gs signaling but not Gq signaling. Molecular dynamics simulations showed that these superficial contacts restrict SP flexibility deep in the NK1R pocket. SP6-11, which lacks these interactions, is dynamic while bound to NK1R. Structural dynamics of NK1R agonists therefore depend on interactions with the receptor extracellular loops and regulate G-protein signaling selectivity. Similar interactions between other neuropeptides and their cognate receptors may tune intracellular signaling.


title: Experimental recommendations for estimating lower extremity loading based on joint and activity

abstract: Researchers often estimate joint loading using musculoskeletal models to solve the inverse dynamics problem. This approach is powerful because it can be done non-invasively, however, it relies on assumptions and physical measurements that are prone to measurement error. The purpose of this study was to determine the impact of these errors - specifically, segment mass and shear ground reaction force - have on analyzing joint loads during activities of daily living. We preformed traditional marker-based motion capture analysis on 8 healthy adults while they completed a battery of exercises on 6 degree of freedom force plates. We then scaled the mass of each segment as well as the shear component of the ground reaction force in 5% increments between 0 and 200% and iteratively performed inverse dynamics calculations, resulting in 1,681 mass-shear combinations per activity. We compared the peak joint moments of the ankle, knee, and hip at each mass-shear combination to the 100% mass and 100% shear combination to determine the percent error. We found that the ankle was most resistant to changes in both mass and shear and the knee was resistant to changes in mass while the hip was sensitive to changes in both mass and shear. These results can help guide researchers who are pursuing lower-cost or more convenient data collection setups.


title: Effective Computational Framework for Pre-Interventional Planning of Peripheral Arteriovenous Malformations with In Vivo and In Vitro Validation

abstract:
PurposePeripheral arteriovenous malformations (pAVMs) are congenital lesions characterised by abnormal high-flow, low-resistance vascular connections - constituting the so-called nidus - between arteries and veins. The mainstay treatment typically involves the embolisation of the nidus with embolic and sclerosant agents, however the complexity of AVMs often leads to uncertain outcomes. This study aims at developing a simple, yet effective computational framework to aid the clinical decision making around the treatment of pAVMs.

MethodsA computational model was developed to simulate the pre-, intra-, and post-intervention haemodynamics of an AVM. A porous medium of varying permeability was used to simulate the effect that the sclerosant has on the blood flow through the nidus. The computational model was informed by computed tomography (CT) scans and digital subtraction angiography (DSA) images, and the results were compared against clinical data and experimental results.

ResultsThe computational model was able to simulate the blood flow through the AVM throughout the intervention and predict (direct and indirect) haemodynamic changes due to the embolisation. The simulated transport of the dye in the AVM was compared against DSA time-series obtained at different intervention stages, providing confidence in the results. Moreover, experimental data obtained via a mock circulatory system involving a patient specific 3D printed phantom of the same AVM provided further validation of the simulation results.

ConclusionWe developed a simple computational framework to simulate AVM haemodynamics and predict the effects of the embolisation procedure. The developed model lays the foundation of a new, computationally driven treatment planning tool for AVM embolisation procedures.


title: High-throughput Raman-activated cell sorting in the fingerprint region

abstract: Cell sorting is the workhorse of biological research and medicine. Cell sorters are commonly used to sort heterogeneous cell populations based on their intrinsic features. Raman-activated cell sorting (RACS) has recently received considerable interest by virtue of its ability to discriminate cells by their intracellular chemical content, in a label-free manner. However, broad deployment of RACS beyond lab-based demonstrations is hindered by a fundamental trade-off between throughput and measurement bandwidth (i.e., cellular information content). Here we overcome this trade-off and demonstrate broadband RACS in the fingerprint region (300 - 1,600 cm-1) with a record high throughput of ~50 cells per second. This represents a 100x throughput increase compared to previous demonstrations of broadband fingerprint-region RACS. To show the utility of our RACS, we demonstrate real-time label-free sorting of microalgal cells based on their accumulation of carotenoids and polysaccharide granules. These results hold promise for medical, biofuel, and bioplastic applications.


title: Structure-Function Relationships of the Vertebral Endplate

abstract:
BackgroundAlthough deformation and fracture of the vertebral endplate have been implicated in spinal conditions such as vertebral fracture and disc degeneration, few biomechanical studies of this structure are available. The goal of this study was to quantify the mechanical behavior of the vertebral endplate.

MethodsEight-five rectangular specimens were dissected from the superior and/or inferior central endplates of human lumbar spine segments L1-L4. Micro-computed tomography (CT) imaging, four-point-bend testing, and ashing were performed to quantify the apparent elastic modulus and yield stress (modulus and yield stress, respectively, of the porous vertebral endplate), tissue yield stress (yield stress of the tissue of the vertebral endplate, excluding pores), ultimate strain, fracture strain, bone volume fraction (BV/TV), bone mineral density (BMD), and various measures of tissue density and composition (tissue mineral density, ash fraction, and ash density). Regression was used to assess the dependence of mechanical properties on density and composition.

ResultsWide variations in elastic and failure properties, and in density and tissue composition, were observed. BMD and BV/TV were good predictors of many of the apparent-level mechanical properties, including modulus, yield stress, and in the case of the inferior vertebral endplate, failure strains. Similar values of the mechanical properties were noted between superior and inferior vertebral endplates. In contrast to the dependence of apparent stiffness and strength on BMD and BV/TV, none of the mechanical properties depended on any of the tissue-level density measurements.

ConclusionThe dependence of many of the mechanical properties of the vertebral endplate on BV/TV and BMD suggests possibilities for non-invasive assessment of how this region of the spine behaves during habitual and injurious loading. Further study of the non-mineral components of the endplate tissue is required to understand how the composition of this tissue may influence the overall mechanical behavior of the vertebral endplate.


title: Detection of fusion transcripts and their genomic breakpoints from RNA sequencing data

abstract: Spliced fusion-transcripts are typically identified by RNA-seq without elucidating the causal genomic breakpoints. However, non poly(A)-enriched RNA-seq contains large proportions of intronic reads spanning also genomic breakpoints. Using 1.274 RNA-seq samples, we investigated what additional information is embedded in non poly(A)-enriched RNA-seq data. Here, we present our novel, graph-based, Dr. Disco algorithm that makes use of both intronic and exonic RNA-seq reads to identify not only fusion transcripts but also genomic breakpoints in gene but also in intergenic regions. Dr. Disco identified TMPRSS2-ERG fusions with genomic breakpoints and other transcribed rearrangements from multiple RNA-sequencing cohorts. In breast cancer and glioma samples Dr. Disco identified rearrangement hotspots near CCND1 and MDM2 and could directly associate this with increased expression. A comparison with matched DNA-sequencing revealed that most genomic breakpoints are not, or minimally, transcribed while also revealing highly expressed translocations missed by DNA-seq. By using the full potential of non poly(A)-enriched RNA-seq data, Dr. Disco can reliably identify expressed genomic breakpoints and their transcriptional effects.


title: DeepImageTranslator: a free, user-friendly graphical interface for image translation using deep-learning and its applications in 3D CT image analysis

abstract:
ObjectivesThe advent of deep-learning has set new standards in an array of image translation applications. At present, the use of these methods often requires computer programming experience. Non-commercial programs with graphical interface usually do not allow users to fully customize their deep-learning pipeline. Therefore, our primary objective is to provide a simple graphical interface that allows students and researchers with no programming experience to easily create, train, and evaluate custom deep-learning models for image translation. We also aimed to test the applicability of our tool (the DeepImageTranslator) in two different tasks: semantic segmentation and noise reduction of CT images.

MethodsThe DeepImageTranslator was implemented using the Tkinter library; backend computations were implemented using Pillow, Numpy, OpenCV, Augmentor, Tensorflow, and Keras libraries. Convolutional neural networks (CNNs) were trained using DeepImageTranslator and assessed with three-way cross-validation. The effects of data augmentation, deep-supervision, and sample size on model accuracy were also systematically assessed.

ResultsThe DeepImageTranslator a simple tool that allows users to customize all aspects of their deep-learning pipeline, including the CNN, the training optimizer, the loss function, and the types of training image augmentation scheme. We showed that DeepImageTranslator can be used to achieve state-of-the-art accuracy and generalizability in semantic segmentation and noise reduction. Highly accurate 3D segmentation models for body composition can be obtained using training sample sizes as small as 17 images. Therefore, for studies with small datasets, researchers can randomly select a very small subset of images for manual labeling, which can then be used to train a specialized CNN model with DeepImageTranslator to fully automate segmentation of the entire dataset, thereby saving tremendous time and effort.

ConclusionsAn open-source deep-learning tool for accurate image translation with a user-friendly graphical interface was presented and evaluated. This standalone software can be downloaded for Windows 10 at: https://sourceforge.net/projects/deepimagetranslator/


title: SCOUR: A stepwise machine learning framework for predicting metabolite-dependent regulatory interactions

abstract:
BackgroundThe topology of metabolic networks is both well-studied and remarkably well-conserved across many species. The regulation of these networks, however, is much more poorly characterized, though it is known to be divergent across organisms - two characteristics that make it difficult to model metabolic networks accurately. While many computational methods have been built to unravel transcriptional regulation, there have been few approaches developed for systems-scale analysis and study of metabolic regulation. Here, we present a stepwise machine learning framework that applies established algorithms to identify regulatory interactions in metabolic systems based on metabolic data: Stepwise Classification Of Unknown Regulation, or SCOUR.

ResultsWe evaluated our framework on both noiseless and noisy data, using several models of varying sizes and topologies to show that our approach is generalizable. We found that, when testing on data under the most realistic conditions (low sampling frequency and high noise), SCOUR could identify reaction fluxes controlled only by the concentration of a single metabolite (its primary substrate) with high accuracy. The positive predictive value (PPV) for identifying reactions controlled by the concentration of two metabolites ranged from 32-88% for noiseless data, 9.2-49% for either low sampling frequency/low noise or high sampling frequency/high noise data, and 6.6-27% for low sampling frequency/high noise data, with results typically sufficiently high for lab validation to be a practical endeavor. While the PPVs for reactions controlled by three metabolites were lower, they were still in most cases significantly better than random classification.

ConclusionsSCOUR uses a novel approach to synthetically generate the training data needed to identify regulators of reaction fluxes in a given metabolic system, enabling metabolomics and fluxomics data to be leveraged for regulatory structure inference. By identifying and triaging the most likely candidate regulatory interactions, SCOUR can drastically reduce the amount of time needed to identify and experimentally validate metabolic regulatory interactions. As high-throughput experimental methods for testing these interactions are further developed, SCOUR will provide critical impact in the development of predictive metabolic models in new organisms and pathways.


title: Pepsickle rapidly and accurately predicts proteasomal cleavage sites for improved neoantigen identification

abstract: Proteasomal cleavage is a key component in protein turnover, as well as antigen presentation and subsequent immune response. Herein we present pepsickle, an open-source tool for proteasomal cleavage prediction with better in vivo prediction performance (AUC) and computational speed than current models available in the field, and with the ability to predict sites based on both constitutive and immunoproteasome profiles. Post-hoc filtering of predicted patient neoepitopes using pepsickle significantly enriches for immune-responsive epitopes and may represent a significant opportunity to improve current epitope prediction and vaccine development pipelines.


title: The role of PI(4,5)P2 and synaptotagmin in membrane fusion - an in vitro study

abstract: Synaptotagmin-1 (syt-1) is known to trigger fusion of neuronal synaptic vesicles with the presynaptic membrane by recognizing acidic membrane lipids. In particular, binding to PI(4,5)P2 is believed to be crucial for its function as a calcium sensor. We propose a mechanism for syt-1 to interact with anionic bilayers and promote fusion in the presence of SNARE proteins. We found that in the absence of Ca2+ the binding of syt-1 to membranes depends on the PI(4,5)P2 content. Addition of Ca2+ switches the interaction forces from weak to strong eventually exceeding the cohesion of the C2A domain, while the interaction between PI(4,5)P2 and the C2B domain was preserved even in the absence of Ca2+ or phosphatidylserine. Fusion of large unilamellar vesicles equipped with syt-1 and synaptobrevin with free-standing target membranes composed of PS/PI(4,5)P2 show an increased fusion speed, and by effective suppression of stalled intermediate states, a larger number of full fusion events. Fusion efficiency could be maximized when irreversible docking is additionally prevented by addition of multivalent anions. The picture that emerges is that syt-1 remodels the membrane in the presence of calcium and PIP2, thereby substantially increasing the efficiency of membrane fusion by avoiding stalled intermediate states.