title: Plague risk in the western United States over seven decades of environmental change

abstract: After several pandemics over the last two millennia, the wildlife reservoirs of plague (Yersinia pestis) now persist around the world, including in the western United States. Routine surveillance in this region has generated comprehensive records of human cases and animal seroprevalence, creating a unique opportunity to test how plague reservoirs are responding to environmental change. Here, we develop a new method to detect the signal of climate change in infectious disease distributions, and test whether plague reservoirs and spillover risk have shifted since 1950. We find that plague foci are associated with high-elevation rodent communities, and soil biochemistry may play a key role in the geography of long-term persistence. In addition, we find that human cases are concentrated only in a small subset of endemic areas, and that spillover events are driven by higher rodent species richness (the amplification hypothesis) and climatic anomalies (the trophic cascade hypothesis). Using our detection model, we find that due to the changing climate, rodent communities at high elevations have become more conducive to the establishment of plague reservoirs--with suitability increasing up to 40% in some places--and that spillover risk to humans at mid-elevations has increased as well, although more gradually. These results highlight opportunities for deeper investigation of plague ecology, the value of integrative surveillance for infectious disease geography, and the need for further research into ongoing climate change impacts.


title: Insights into biotic and abiotic modulation of ocean mesopelagic communities

abstract: Marine plankton mitigate anthropogenic greenhouse gases, modulate biogeochemical cycles, and provide fishery resources. Plankton is distributed across a stratified ecosystem of sunlit surface waters and a vast, though understudied, mesopelagic  dark ocean. In this study, we mapped viruses, prokaryotes, and pico-eukaryotes across 32 globally-distributed cross-depth samples collected during the Tara Oceans Expedition, and assessed their ecologies. Based on depth and O2 measurements, we divided the marine habitat into epipelagic, oxic mesopelagic, and oxygen minimum zone (OMZ) eco-regions. We identified specific communities associated with each marine habitat, and pinpoint environmental drivers of dark ocean communities. Our results indicate that water masses primarily control mesopelagic community composition. Through co-occurrence network inference and analysis, we identified signature communities strongly associated with OMZ eco-regions. Mesopelagic communities appear to be constrained by a combination of factors compared to epipelagic communities. Thus, variations in a given abiotic factor may cause different responses in sunlit and dark ocean communities. This study expands our knowledge about the ecology of planktonic organisms inhabiting the mesopelagic zone.

category: ecology


title: Seasonal dynamics are the major driver of microbial diversity and composition in intensive freshwater aquaculture

abstract:
Aquaculture facilities such as fishponds are one of the most anthropogenically impacted freshwater ecosystems. The high fish biomass reared in aquaculture is associated with an intensive input into the water of fish-feed and fish excrements. This nutrients load may affect the microbial community in the water, which in turn can impact the fish health. To determine to what extent aquaculture practices and natural seasonal cycles affect the microbial populations, we characterized the microbiome of an inter-connected aquaculture system at monthly resolution, over three years. The system comprised two fishponds, where fish are grown, and a "control" operational water reservoir in which fish are not actively stocked. Clear natural seasonal cycles of temperature and inorganic nutrients concentration, as well as recurring cyanobacterial blooms during summer, were observed in both the fishponds and the reservoir. The structure of the aquatic bacterial communities in the system, characterized using 16S rRNA sequencing, was explained primarily by the natural seasonality, whereas aquaculture-related parameters had only a minor explanatory power. However, the cyanobacterial blooms were characterized by different cyanobacterial clades dominating at each fishpond, possibly in response to distinct nitrogen and phosphate ratios. In turn, nutrient ratios may have been by the magnitude of fish feed input. Taken together, our results show that, even in strongly anthropogenically impacted aquatic ecosystems, the structure of bacterial communities is mainly driven by the natural seasonality, with more subtle effects if aquaculture-related factors.

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=114 SRC="FIGDIR/small/433039v1_ufig1.gif" ALT="Figure 1">
View larger version (39K):
org.highwire.dtl.DTLVardef@154d693org.highwire.dtl.DTLVardef@d35ae9org.highwire.dtl.DTLVardef@1f5a7a2org.highwire.dtl.DTLVardef@d07fbc_HPS_FORMAT_FIGEXP  M_FIG C_FIG HighlightsO_LIWe present three years of monthly microbiome data from an aquaculture facility.
C_LIO_LIThe microbiome changes seasonally, likely driven by temperature and rainwater runoff.
C_LIO_LISummer blooms of toxin-producing cyanobacteria are repeatedly observed.
C_LIO_LIFish food may impact microbiome through changes in nutrient ratios.
C_LI


title: Molecular response of whitefly to the wild tomato Solanum habrochaites

abstract: The whitefly Bemisia tabaci (Gennadius) causes severe damage to cultivated tomato in many regions of the world through direct feeding and indirectly through transmission of plant viruses. Field observations show that B. tabaci is rarely infested the non-host plants such as the wild tomato Solanum habrochaites; however, the molecular mechanism involved in the recognition of wild plant odors is still unclear. In this study, we assessed the effects of S. habrochaites on the survival, fecundity, and egg hatchability of the Mediterranean (MED) species of B. tabaci. Expression and splicing of stress-response genes in whitefly exposed to S. habrochaites was analyzed using RNA-sequencing data and alternative splicing analysis. These results indicated that the S. habrochaites treatment can induce the expression of environmental stress genes in B. tabaci. This study may help us to a better understanding of the molecular mechanisms involved in the olfactory recognition of non-host volatiles particularly wild tomato relative. Furthermore, the findings of this study may provide excellent chances of finding a suitable antagonist of eco-friendly properties which can block the perception of chemosensory signals. Thereby, the feeding behavior and food preferences of B. tabaci can be manipulated and thus insect populations can eventually be controlled.


title: Response of whitefly to the wild tomato Solanum habrochaites


title: Ionotropic receptors in the turnip moth Agrotis segetum respond to repellent medium-chain fatty acids

abstract:
BackgroundIn insects, airborne chemical signals are mainly detected by two receptor families, odorant receptors (ORs) and ionotropic receptors (IRs). Functions of ORs have been intensively investigated in Diptera and Lepidoptera, while the functions and evolution of the more ancient IR family remain largely unexplored beyond Diptera.

ResultsHere, we identified a repertoire of 26 IRs from transcriptomes of female and male antennae, and ovipositors in the moth Agrotis segetum. We observed that a large clade formed by IR75p and IR75q expansions is closely related to the acid-sensing IRs identified in Diptera. We functionally assayed each of the five AsegIRs from this clade using Xenopus oocytes and found that two receptors responded to the tested ligands. AsegIR75p.1 responded to several compounds but hexanoic acid was revealed to be the primary ligand, and AsegIR75q.1 responded primarily to octanoic acid, and less so to nonanoic acid. It has been reported that the C6-C10 medium-chain fatty acids repel various insects including many drosophilids and mosquitos. Our GC-EAD recordings showed that C6-C10 medium-chain fatty acids elicited antennal responses of both sexes of A. segetum, while only octanoic acid had repellent effect to the moths in a behavioural assay. In addition, using fluorescence in situ hybridization, we demonstrated that the five IRs and their co-receptor AsegIR8a are not located in coeloconic sensilla as found in Drosophila, but in basiconic or trichoid sensilla.

ConclusionsOur results significantly expand the current knowledge of the insect IR family. Based on the functional data in combination with phylogenetic analysis, we propose that subfunctionalization after gene duplication plays an important role in the evolution of ligand specificities of the acid-sensing IRs in Lepidoptera.

category: evolutionary biology


title: Phylogenomic Analyses Of 2,786 Genes In 158 Lineages Support a Root of The Eukaryotic Tree of Life Between Opisthokonts (Animals, Fungi and Their Microbial Relatives) and All Other Lineages

abstract:
Advances in phylogenetics and high-throughput sequencing have allowed the reconstruction of deep phylogenetic relationships in the evolution of eukaryotes. Yet, the root of the eukaryotic tree of life remains elusive. The most popular hypothesis in textbooks and reviews is a root between Unikonta (Opisthokonta + Amoebozoa) and Bikonta (all other eukaryotes), which emerged from analyses of a single gene fusion. Subsequent highly-cited studies based on concatenation of genes supported this hypothesis with some variations or proposed a root within Excavata. However, concatenation of genes neither considers phylogenetically-informative events (i.e. gene duplications and losses), nor provides an estimate of the root. A more recent study using gene tree-species tree reconciliation methods suggested the root lies between Opisthokonta and all other eukaryotes, but only including 59 taxa and 20 genes. Here we apply a gene tree - species tree reconciliation approach to a gene-rich and taxon-rich dataset (i.e. 2,786 gene families from two sets of ~158 diverse eukaryotic lineages) to assess the root, and we iterate each analysis 100 times to quantify tree space uncertainty. We estimate a root between Fungi and all other eukaryotes, or between Opisthokonta and all other eukaryotes, and reject alternative roots from the literature. Based on further analysis of genome size we propose Opisthokonta + others as the most likely root.

Impact summaryFinding the root of the eukaryotic tree of life is critical for the field of comparative biology as it allows us to understand the timing and mode of evolution of characters across the evolutionary history of eukaryotes. But this is one of the most challenging questions in evolutionary biology because the age (~1.8 billion years), diversity and complexity of eukaryotes challenge phylogenomic methods. This study evaluates the root using reconciliation of gene trees and species trees instead of the more common approach of analyzing concatenated genes. The dataset used in this study is bigger and more taxonomically inclusive than the dataset of any previous study about the eukaryotic root, and supports a root at or within Opisthokonta (e.g. animals and fungi). Finally, we explicitly test alternative hypotheses from the literature, and again find support for an Opisthokonta root.


title: Drivers of adaptive capacity in wild populations: implications for genetic interventions

abstract: The unprecedented rate of environmental change in the Anthropocene poses evolutionary challenges for wild populations globally. Active human interventions are being increasingly considered to accelerate natural adaptive processes. Evolutionary models can evaluate how species may fare under future climate, elucidate which evolutionary processes are critical to rapid adaptation, and how active interventions may influence fitness trajectories of organisms. Here we use polygenic metapopulation adaptation models to quantify the relative importance (effect sizes) of different eco-evolutionary parameters on the rates of adaptation in wild populations i) without active interventions, and ii) under a subset of active interventions. We demonstrate that genetic diversity (heterozygosity, He), population connectivity and the effect size of additive genetic variance are the primary drivers of natural adaptation rates. We quantify the effect sizes of these parameters on population fitness across three proposed assisted evolution scenarios and identify critical thresholds for intervention effectiveness and implementation. Specifically, the interventions tested here were most effective at low levels of genetic diversity in target populations (He < 0.2) and when timed during a cold-to-warm phase of an ENSO-like oscillation. Beneficial levels of connectivity were highly dependent on desired outcomes for the meta-population. We also present a global meta-analysis of genetic diversity in tropical reef-building corals as a case study of how thresholds derived from evolutionary models can be used to guide decision making by managers. We find genetic diversity to be highly variable by coral taxon and region, highlighting how thresholds from evolutionary models can be used in conjunction with empirical data to assess intervention needs and priorities. Finally, we highlight the critical knowledge and data gaps to produce the next suite of applied models for conservation management decision-support.


title: Multiple Loci Selection with Multi-way Epistasis in Coalescence with Recombination

abstract: As studies move into deeper characterization of the impact of selection through non-neutral mutations in whole genome population genetics, modeling for selection becomes crucial. Moreover, epistasis has long been recognized as a significant component in understanding evolution of complex genetic systems. We present a backward coalescent model EpiSimRA, that builds multiple loci selection, with multi-way (k-way) epistasis for any arbitrary k. Starting from arbitrary extant populations with epistatic sites, we trace the Ancestral Recombination Graph (ARG), sampling relevant recombination and coalescent events. Our framework allows for studying different complex evolutionary scenarios in the presence of selective sweeps, positive and negative selection with multiway epistasis. We also present a forward counterpart of the coalescent model based on a Wright-Fisher (WF) process which we use as a validation framework, comparing the hallmarks of the ARG between the two. We provide the first framework that allows a nose-to-nose comparison of multiway epistasis in a coalescent simulator with its forward counterpart with respect to the hallmarks of the ARG. We demonstrate through extensive experiments, that EpiSimRA is consistently superior in term of performance (seconds vs. hours) in comparison to the forward model without compromising on its accuracy. EpiSimRA (both backward and forward) source, executable, user manuals are available at: https://github.com/ComputationalGenomics/SimRA.

category: genomics


title: Genomic analyses of the extinct Sardinian dhole (Cynotherium sardous) reaveal its evolutionary history

abstract:
The Sardinian dhole (Cynotherium sardous)1 was an iconic and unique canid species of canid that was endemic of Sardinia and Corsica until it became extinct at the end of the Late Pleistocene2-5. Given its peculiar dental morphology, small body size and high level of endemism, several canids have been proposed as possible ancestors of the Sardinian dhole, including the Asian dhole and African hunting dog ancestor 3,6-9. Morphometric analyses3,6,8-12 have failed to clarify the evolutionary relationship with other canids.

We sequenced the genome of a ca 21,100 year old Sardinian dhole in order to understand its genomic history and clarify its phylogenetic position. We found it represents a separate taxon from all other living canids from Eurasia, Africa and North America, and that the Sardinian and Asian dhole lineages diverged ca 885 ka. We additionally detected historical gene flow between the Sardinian and Asian dhole lineages, that ended approximately 500-300 ka, when the landbridge between Sardinia and mainland Italy was broken, severing their population connectivity. Our sample showed low genome-wide diversity compared to other extant canids - probably a result of the long-term isolation - that could have contributed to the subsequent extinction of the Sardinian dhole.


title: Distribution of methionine sulfoxide reductases in fungi and conservation of the free-methionine-R-sulfoxide reductase in multicellular eukaryotes

abstract:
Methionine, either as a free amino acid or included in proteins, can be oxidized into methionine sulfoxide (MetO), which exists as R and S diastereomers. Almost all characterized organisms possess thiol-oxidoreductases named methionine sulfoxide reductase (Msr) enzymes to reduce MetO back to Met. MsrA and MsrB reduce the S and R diastereomers of MetO, respectively, with strict stereospecificity and are found in almost all organisms. Another type of thiol-oxidoreductase, the free-methionine-R-sulfoxide reductase (fRMsr), identified so far in prokaryotes and a few unicellular eukaryotes, reduces the R MetO diastereomer of the free amino acid. Moreover, some bacteria possess molybdenum-containing enzymes that reduce MetO, either in the free or protein-bound forms. All these Msrs play important roles in the protection of organisms against oxidative stress. Fungi are heterotrophic eukaryotes that colonize all niches on Earth and play fundamental functions, in organic matter recycling, as symbionts, or as pathogens of numerous organisms. However, our knowledge on fungal Msrs is still limited. Here, we performed a survey of msr genes in almost 700 genomes across the fungal kingdom. We show that most fungi possess one gene coding for each type of methionine sulfoxide reductase: MsrA, MsrB, and fRMsr. However, several fungi living in anaerobic environments or as obligate intracellular parasites were devoid of msr genes. Sequence inspection and phylogenetic analyses allowed us to identify non-canonical sequences with potentially novel enzymatic properties. Finaly, we identified several ocurences of msr horizontal gene transfer from bacteria to fungi.

HighlightsO_LIFree and protein-bound methionine can be oxidized into methionine sulfoxide (MetO).
C_LIO_LIMethionine sulfoxide reductases (Msr) reduce MetO in most organisms.
C_LIO_LISequence characterization and phylogenomics revealed strong conservation of Msr in fungi.
C_LIO_LIfRMsr is widely conserved in unicellular and multicellular fungi.
C_LIO_LISome msr genes were acquired from bacteria via horizontal gene transfers.
C_LI


title: Insulin-like peptide receptor mediated signaling pathways orchestrate regulation of energy homeostasis in the Pacific oyster, Crassostrea gigas

abstract:
The involvement of insulin/insulin-like growth factor (IIS) signaling pathway in growth regulation of marine invertebrates remains largely unexplored. In this study, we used a fast-growing Pacific oyster (Crassostrea gigas) variety "Haida No.1" as material to unravel the role of IIS system in growth regulation in oysters. Systematic bioinformatics analyses allowed to identify major components of IIS signaling pathway and insulin-like peptide receptor (ILPR) mediated signaling pathways, including PI3K-AKT, RAS-MAPK, and TOR, in C. gigas. Expression levels of the major genes in IIS and its downstream signaling pathways were significantly higher in "Haida No.1" than wild oysters, suggesting their involvement in growth regulation of C. gigas. Expression profiles of IIS and its downstream signaling pathway genes were significantly altered by nutrient abundance and culture temperature. These results suggested that IIS signaling pathway coupled with the ILPR mediated signaling pathways orchestrated energy homeostasis to regulate growth in the Pacific oyster.

Research HighlightsO_LIILPR, IRS, IGFBPRP, and IGFALS genes were characterized in the C. gigas.
C_LIO_LIMajor genes of IIS signaling pathway were highly expressed in fast-growing C. gigas.
C_LIO_LIIIS and downstream pathways participates in energy homeostasis of oysters.
C_LIO_LIILPR mediated signaling pathways orchestrate growth regulation in oysters.
C_LI


title: Discover Your Potential: The Influence of Kinematics on a Muscle's Ability to Contribute to the Sit-to-Stand Transfer

abstract: Existing methods for estimating how individual muscles contribute to a movement require extensive time and experimental resources. In this study we developed an efficient method for determining how changes to lower extremity joint kinematics affect the potential of individual muscles to contribute to whole-body center-of-mass vertical (support) and anteroposterior (progression) accelerations. A 4-link 2-dimensional model was used to assess the effect of kinematic changes on muscle function. Joint kinematics were systematically varied throughout ranges observed during the momentum transfer phase of the sit-to-stand transfer. Each muscles potential to contribute to support and progression was computed and compared to simulated potentials estimated by traditional dynamic simulation methods for young adults and individuals with knee osteoarthritis (KOA). The new method required 4-10s to compute muscle potentials per kinematic state and computed potentials were consistent with simulated potentials. The new method identified differences in muscle potentials between groups due to kinematic differences, particularly decreased anterior pelvic tilt in young adults, and revealed kinematic and muscle strengthening modifications to increase support. The methods presented provide an efficient, systematic approach to evaluate how joint kinematic adjustments alter a muscles ability to contribute to movement and can identify potential sources of pathologic movement and rehabilitation strategies.

category: bioengineering


title: Segmentation of the Urothelium in Optical Coherence Tomography Images with Dynamic Contrast

abstract:
SignificanceSpeckle variations induced by intracellular motion (IM) in the urothelium was observed in optical coherence tomography (OCT) images. It is feasible to use the IM as a dynamic contrast to segment the urothelium with only two sequential OCT images. This new method opens the possibility of tracking the distribution of the urothelial cells to identify the microinvasion of bladder tumors.

ApproachWith fresh porcine bladder tissue, IM was analyzed by tracking speckle variations using autocorrelation function, then quantified with CONTINE algorism to identify the decorrelation time (DT) of the speckle variations. Variance analysis is conducted to show IM amplitude and distribution in the urothelium. The segmentation of the urothelium is demonstrated using tissue samples with and without significantly stretching.

ResultsSignificant speckle variations induced by IM exists in the urothelium. However, the distribution of the IM is heterogeneous. The DTs are majorly distributed between 1ms to 30ms. Using the IM as a dynamic contrast, the urothelium can be accurately and exclusively segmented, even the layer structure of the bladder is invisible.

ConclusionsWith fresh porcine bladders, we show that IM can be used as a dynamic contrast to exclusively segment the urothelium. This contrast may provide a new mechanism for OCT to diagnosis the invasion of urothelial cancerous cells for the better staging of bladder cancer.


title: Machine learning for cell classification and neighborhood analysis in glioma tissue

abstract: Multiplexed and spatially resolved single-cell analyses that intend to study tissue heterogeneity and cell organization invariably face as a first step the challenge of cell classification. Accuracy and reproducibility are important for the down-stream process of counting cells, quantifying cell-cell interactions, and extracting information on disease-specific localized cell niches. Novel staining techniques make it possible to visualize and quantify large numbers of cell-specific molecular markers in parallel. However, due to variations in sample handling and artefacts from staining and scanning, cells of the same type may present different marker profiles both within and across samples. We address multiplexed immunofluorescence data from tissue microarrays of low grade gliomas and present a methodology using two different machine learning architectures and features insensitive to illumination to perform cell classification. The fully automated cell classification provides a measure of confidence for the decision and requires a comparably small annotated dataset for training, which can be created using freely available tools. Using the proposed method, we reached an accuracy of 83.1% on cell classification without the need for standardization of samples. Using our confidence measure, cells with low-confidence classifications could be excluded, pushing the classification accuracy to 94.5%. Next, we used the cell classification results to search for cell niches with an unsupervised learning approach based on graph neural networks. We show that the approach can re-detect specialized tissue niches in previously published data, and that our proposed cell classification leads to niche definitions that may be relevant for sub-groups of glioma, if applied to larger datasets.

category: bioinformatics


title: On bridging paired-end RNA-seq data

abstract:
MotivationThe widely-used high-throughput RNA-sequencing technologies (RNA-seq) usually produce paired-end reads. We explore if full fragments can be computationally reconstructed from the sequenced two ends--a problem here we refer to as bridging. Solving this problem provides longer, more informative RNA-seq reads, and hence benefits downstream RNA-seq analysis such as transcriptome assembly and expression quantification. However, bridging is a challenging and complicated task owing to alternative splicing, transcript noises, and sequencing errors. It remains unclear if the data itself provides sufficient information for accurate bridging, let alone proper models and efficient algorithms that characterize and determine the true bridges.

Algorithmic ResultsWe studied this problem in two settings: reference-based bridging, which assumes reads alignments are available and reconstructs the alignments of full fragments, and de novo bridging, which reconstructs sequences of entire fragments from sequences of the two ends. We proposed a novel mathematical formulation that works for both settings--to seek a path in an underlying graph data structure (i.e., splice graph for reference-based bridging, and compacted de Bruijn graph for de novo bridging) such that its bottleneck weight is maximized. This formulation characterizes true bridges and is efficient in filtering out false bridges. This formulation admits optimal substructure property, and hence efficient dynamic programming algorithms can be designed. For reference-based bridging, we designed such an algorithm to calculate the top N bridging paths, followed by a voting approach to select one using the distribution of fragment length. For de novo bridging, we designed a new truncated Dijkstras algorithm. To further speed up, we proposed a novel algorithm that reuses the shortest path tree to avoid running the truncated Dijkstras algorithm from scratch for all vertices. These innovations result in scalable algorithms that can bridge all paired-end reads in a compacted de Bruijn graph with millions of vertices.

Experimental ResultsWe showed that paired-end RNA-seq reads can be accurately bridged to a large extend. Our reference-based bridging tool could correctly bridge more than 79.6% of reads. For de novo bridging, high precision was observed with varied sensitivity. We also showed that bridging can improve reference-based transcript assembly: the improvement was significant (up to 14.4% measured with adjusted precision), and universal in all combinations with different aligners and assemblers.

AvailabilityImplementations of the algorithms for reference-based and de novo bridging are available at https://github.com/Shao-Group/rnabridge-align and https://github.com/Shao-Group/rnabridge-denovo, respectively. Scripts, datasets, and documentations that can reproduce the experimental results in this manuscript are available at https://github.com/Shao-Group/rnabridge-test.


title: Chasing the cardiomyopathy modifier genes: Integrative computational analysis interweave the missing links in cardiomyopathy diseasome

abstract:
BackgroundCardiomyopathies are genetic disorders resulting in an abnormal heart phenotype due to intrinsic cardiac muscle malfunction, which leads to heart failure. These are chronic disorders contributing more than 36% of heart failure in the patients. Cardiomyopathies also show co-morbidity with other diseases that frequently affect the elderly. Apart from this, many drugs used for treating other unrelated diseases cause cardio-toxicity and lead to cardiomyopathies. Unravelling the cross-talk between them is essential for useful characterization, subtyping, and better treatment of the cardiomyopathies.

ResultsIn this work, we applied a systems biology-based analysis to explore the associations between cardiomyopathies and other morbidities. We built a cardiomyopathy disease-disease network based on the combined biological data relevant to cardiomyopathies. We made use of publicly available genetic, non-coding RNA, drug and PPI datasets related to cardiomyopathies and network science tools to identify new modifiers genes that may have a role in cardiomyopathies. These modifier genes are further enriched using mouse phenotype data. We highlight key modifier genes that are potentially associated with cardiomyopathies. Many predicted genes link cardiomyopathies to neoplasms, metabolic and neurological disorders, some of these have been detailed as case studies in this analysis.

ConclusionsTraditional one drug-one target-one disease outlook alone in drug discovery is challenging. We hereby develop an integrative approach based on primary cardiomyopathy target genes to discover new targets. These can provide clues in drug repurposing, possible off-targets and hidden genetic overlap between cardiomyopathies and other morbidities. We report potential modifier genes like NOTCH4 and SIRT1 that may be investigated for their role in cardiomyopathy and other diseases.


title: Computational analysis of vertebrate myoglobins reveals aggregation resistance in aquatic birds and higher surface hydrophobicity in fish

abstract: Myoglobin is the major oxygen carrying protein of vertebrate muscle, and high myoglobin net charge is known to hold evolutionary significance as a molecular signature of secondarily aquatic diving capacity in mammals. However, the evolution of myoglobins electrostatic properties in non-mammalian vertebrates, such as birds, has not been investigated. Here, we used a new deep learning-based protein folding algorithm to model the tertiary structures of myoglobin from 302 vertebrate species and performed a comparative analysis of their net charge, positively charged solvent-accessible surface area, and negatively charged solvent-accessible surface area. For avian myoglobins, we also calculated selection pressure ({omega}). The results suggest that the myoglobins of diving avians, specifically those of the penguins (Sphenisciformes) and diving ducks (Aythyini), have highly positively charged electrostatic surfaces, which evolved via positive selection to reduce aggregation propensity and allow greater storage of oxygen for extended underwater foraging. In contrast, galliform myoglobins are under high purifying selection. Distribution of charged atoms on myoglobin surface was more indicative of high myoglobin content than net charge. We also found inter-class differences in net charge; bird myoglobins are the most positively charged and reptile and amphibian myoglobins are the most negatively charged, and net charge seems to be negatively associated with herbivory within mammals. Finally, we propose an equation that describes the relationship between myoglobin net charge and concentration better than the previously suggested logarithmic function. Our findings offer novel insights into the diversification of myoglobin in vertebrate clades and highlight the power of computational structural approaches for zoological and evolutionary research.


title: Evolution of myoglobin in avian lineages: positive selection for aggregation resistance in penguins and high purifying selection in galliforms


title: DENTIST - using long reads to close assembly gaps at high accuracy

abstract:
BackgroundLong sequencing reads allow increasing contiguity and completeness of fragmented, short-read based genome assemblies by closing assembly gaps, ideally at high accuracy. While several gap closing methods have been developed, these methods often close an assembly gap with sequence that does not accurately represent the true sequence.

FindingsHere, we present DENTIST, a sensitive, highly accurate and automated pipeline method to close gaps in short-read assemblies with long error-prone reads. DENTIST comprehensively determines repetitive assembly regions to identify reliable and unambiguous alignments of long reads to the correct loci, integrates a consensus sequence computation step to obtain a high base accuracy for the inserted sequence, and validates the accuracy of closed gaps. Unlike previous benchmarks, we generated test assemblies that have gaps at the exact positions where real short-read assemblies have gaps. Generating such realistic benchmarks for Drosophila (134 Mb genome), Arabidopsis (119 Mb), hummingbird (1 Gb) and human (3 Gb) and using simulated or real PacBio continuous long reads, we show that DENTIST consistently achieves a substantially higher accuracy compared to previous methods, while having a similar sensitivity.

ConclusionDENTIST provides an accurate approach to improve the contiguity and completeness of fragmented assemblies with long reads. DENTISTs source code including a Snakemake workflow, conda package and Docker container is available at https://github.com/a-ludi/dentist. All test assemblies as a resource for future benchmarking are at https://bds.mpi-cbg.de/hillerlab/DENTIST/.


title: DENTIST - using long reads for closing assembly gaps at high accuracy


title: VCFCons: a versatile VCF-based consensus sequence generator for small genomes

abstract: We had developed VCFCons to address urgent need for a robust consensus sequence generator for SARS-CoV-2 viral surveillance, which presented several unique requirements, including: (a) low coverage areas should be noted with  Ns, (b) low frequency or suspicious variant calls need to be filtered. We have found that, while some existing tools such as bcftools can generate the desired consensus sequence, it required multiple filtering steps and additional scripting. VCFCons can generate consensus sequences based on variant calls in a VCF format with versatile filtering criteria based on coverage and estimated variant frequency. We applied VCFCons to the Labcorp SARS-CoV-2 sequencing data and showed that it generated correct consensus sequences that were successfully submitted to GISAID and NCBI. We hope the community will find value in this tool and aim to continue developing VCFCons to handle more complex viral data in the future.


title: Podophyllotoxin And Quercetin In Silico Derivatives Docking Analysis With Cyclooxygenase-2 And Aminopeptidase-N

abstract: The cyclooxygenase (COX) enzymes are tumor markers, the inhibition of which can be used in the prevention and therapy of carcinogenesis. It was found that COX-2 IS considered as targets for tumor inhibition. Aminopeptidase N (APN) is a type II membrane-bound metalloprotease associated with cancer, being identified as a cell marker on the surface of malignant myeloid cells and reached a high level of expression in progressive tumors. In anticancer therapy, plant compounds are considered that can inhibit their activity. Modeling of the COX-2 and APN enzymes was carried out on the basis of molecular models of three-dimensional structures from the PDB database [PDB ID: 5f19, 4fyq] RCSB. For docking analysis, 3D ligand models were created using MarvinSketch based on the PubChem database [CID: 5280343, 5281654]. In silico experiments, for the first time, revealed the possible interaction and inhibition of COX-2 and APN by quercetin and quercetin derivatives. Aspirin and Marimastat were taken to compare the results. Possible biological activities and possible side effects of the ligands have been identified.


title: GUIdeStaR (G-quadruplex, Uorf, IRES, Small RNA, Repeats), bioinformatics tool for gene characterization- case study: development of attribute selection and classification methods based on GuideStar for studying human transcription factor genes mediated by SARS-COV-2 small ncRNA

abstract: GUIdEStaR integrates existing databases of various types of G-quadruplex, upstream Open Reading Frame (uORF), Internal Ribosome Entry Site (IRES), methylation to RNA and histone protein, small RNA, and repeats. GUIdEStaR consists of approx. 40,000 genes and 320,000 transcripts. An mRNA transcript is divided into 5 regions (5UTR, 3UTR, exon, intron, and biological region) where each region contains presence-absence data of 169 different types of elements. Recently, artificial intelligence (AI) based analysis of sequencing data has been gaining popularity in the area of bioinformatics. GUIdEStaR generates datasets that can be used as inputs to AI methods. At the GUIdEStaR homepage, users submit gene symbols by clicking a "Send" button, and shortly result files in CSV format are available for download at the result website. Users have an option to send the result files to their email addresses. Additionally, the entire database and the example Java codes are also freely available for download. Here, we demonstrate the database usage with three neural network classification studies-1) small RNA study for classifying transcription factor (TF) genes into either one of TF mediated by small RNA originated from SARS-CoV-2 or by human microRNA (miRNA), 2) cell membrane receptor study for classifying receptor genes as either with virus interaction or without one, and 3) nonsense mediated mRNA decay (NMD) study for classifying cell membrane and nuclear receptors as either NMD target or non-target. GUIdEStaR is available for access to the easy-to-use web-based database at www.guidestar.kr and for download at https://sourceforge.net/projects/guidestar.


title: GUIdEStaR (G-quadruplex, uORF, IRES, Epigenetics, Small RNA, Repeats), the integrated matadatabase: transcript-indexed binary information creation for chaining with neural network analysis


title: GUIdEStaR (G-quadruplex, uORF, IRES, Epigenetics, Small RNA, Repeats), the integrated metadatabase in conjunction with neural network methods


title: Discovering differential genome sequence activity with interpretable and efficient deep learning

abstract:
Discovering sequence features that differentially direct cells to alternate fates is key to understanding both cellular development and the consequences of disease related mutations. We introduce Expected Pattern Effect and Differential Expected Pattern Effect, two black-box methods that can interpret genome regulatory sequences for cell type-specific or condition specific patterns. We show that these methods identify relevant transcription factor motifs and spacings that are predictive of cell state-specific chromatin accessibility. Finally, we integrate these methods into framework that is readily accessible to non-experts and available for download as a binary or installed via PyPI or bioconda at https://cgs.csail.mit.edu/deepaccess-package/.

Author SummaryWithin the genome are the instructions to build all the cell types that make up the human body. However, understanding these instructions and how and when these instructions go wrong in cancer or genetically inherited disease is an open problem. Deep neural networks provide powerful models to learn the relationship between DNA sequence and functional consequence across many different cell types, such as whether a particular stretch of DNA is accessible and genes in that region can be expressed or is inaccessible and therefore genes are inactive. Despite these advances, a major setback in deep learning is that it is challenging to understand what patterns of DNA sequences a deep learning model has learned to associate with a particular genomic function, whether these patterns are significant, and how to determine whether these patterns are specific to a particular cell type or are general "housekeeping" patterns that function across many cell types. We introduce Expected Pattern Effect and Differential Expected Pattern Effect, two methods which allow us to evaluate the significance of particular patterns of DNA sequence features on models trained to predict function across multiple cell types, and apply this to problems of transcription factor binding and DNA accessibility across multiple cell types.


title: Sequence-unrelated long noncoding RNAs converged to modulate the activity of conserved epigenetic machineries across kingdoms

abstract: RNA-DNA hybrid (R-loop)-associated long noncoding RNAs (lncRNAs), including the Arabidopsis lncRNA AUXIN-REGULATED PROMOTER LOOP (APOLO), are emerging as important regulators of three-dimensional chromatin conformation and gene transcriptional activity. Here, we showed that in addition to the PRC1-component LIKE-HETEROCHROMATIN PROTEIN 1 (LHP1), APOLO interacts with the methylcytosine-binding protein VARIANT IN METHYLATION 1 (VIM1), a conserved homolog of the mammalian DNA methylation regulator UBIQUITIN-LIKE CONTAINING PHD AND RING FINGER DOMAINS 1 (UHRF1). The APOLO-VIM1-LHP1 complex directly regulates the transcription of the auxin biosynthesis gene YUCCA2 by dynamically determining DNA methylation and H3K27me3 deposition over its promoter during the plant thermomorphogenic response. Strikingly, we demonstrated that the lncRNA UHRF1 Protein Associated Transcript (UPAT), a direct interactor of UHRF1 in humans, can be recognized by VIM1 and LHP1 in plant cells, despite the lack of sequence homology between UPAT and APOLO. In addition, we showed that increased levels of APOLO or UPAT hamper VIM1 and LHP1 binding to YUCCA2 promoter. Collectively, our results uncover a new mechanism in which a plant lncRNA coordinates Polycomb action and DNA methylation, and reveal that evolutionary unrelated lncRNAs may exert similar functions across kingdoms.

category: plant biology


title: Gene regulatory networks for compatible versus incompatible grafts identify a role for SlWOX4 during junction formation

abstract: Graft incompatibility is a poorly understood phenomenon that presents a serious agricultural challenge. Unlike immediate incompatibility that results in rapid death, delayed incompatibility can take months or even years to manifest, creating a significant economic burden for perennial crop production. To gain insight into the genetic mechanisms underlying this phenomenon, we developed a model system with Solanum lycopersicum  tomato and Capsicum annuum  pepper heterografting, which expresses signs of anatomical junction failure within the first week of grafting. By generating a detailed timeline for junction formation we were able to pinpoint the cellular basis for this delayed incompatibility. Furthermore, we infer gene regulatory networks for compatible self-grafts versus incompatible heterografts based on these key anatomical events, which predict core regulators for grafting. Finally, we delve into the role of vascular development in graft formation and validate SlWOX4 as a regulator for grafting in tomato. Notably, SlWOX4 is the first gene to be functionally implicated in vegetable crop grafting.


title: Multidimensional molecular differences between artificial and wild Artemisia rupestris L.

abstract:
Different ecological environments affect the active ingredients and molecular content of medicinal plants. Artemisia rupestris L. is a kind of traditional medicinal plant, and the shortages of the wild resource have led to increased use of artificial varieties. However, there have few investigations referring to molecular differences between them in a systematic manner. In the present study, artificial and wild Artemisia rupestris L. plants were collected in the Altay-Fuyun region, Xinjian, China. Untargeted metabolomics method based on liquid chromatography-mass spectrometry (LC-MS) technology was applied to profile flower, stem, and leaf samples, respectively, and levels of a panel of representative known metabolites in this plant were simultaneously analyzed. The genetic basis of these samples was explored using a de novo transcriptomics approach to investigate differentially expressed genes (DEGs) and their pathway annotations. Results indicated metabolic differences between the two varieties mainly reflected in flavonoids and chlorogenic acid/caffeic acid derivatives. 34 chemical markers (CMs) belonging to these two structural categories were discovered after validation using another batch of samples, including 19 potentially new compounds. After correlation analysis, total of six DEGs in different organs relating to 24 CMs were confirmed using quantitative real-time PCR (qPCR). These findings provided novel insight into the molecular landscape of this medicinal plant through metabolomics-transcriptomics integration strategy, and reference information of its quality control and species identification.

ONE SENTENCE SUMMARYA metabolomics-transcriptomics research on Artemisia rupestris L. to discover metabolite differences and the genetic basis between artificial and wild varieties in systematic and novel manner.

category: systems biology


title: Improved correspondence of fMRI visual field localizer data after macroanatomical alignment

abstract: Studying the visual system with fMRI often requires using localizer paradigms to define regions of interest (ROIs). However, the considerable interindividual variability of the cerebral cortex represents a crucial confound for group-level analyses. Cortex-based alignment (CBA) techniques reliably reduce interindividual macroanatomical variability. Yet, their utility has not been assessed for visual field localizer paradigms, which map specific parts of the visual field within retinotopically organized visual areas. We evaluated CBA for an attention-enhanced visual field localizer mapping homologous parts of each visual quadrant in 50 participants. We compared CBA with volume-based alignment and a surface-based analysis, which did not include macroanatomical alignment. CBA led to the strongest increase in the probability of activation overlap (up to 40 percent). On the group level, CBA led to the most consistent increase in ROI size while preserving vertical ROI symmetry. Overall, our results indicate, that in addition to the increased signal-to-noise ratio of a surface-based analysis macroanatomical alignment considerably improves statistical power. These findings confirm and extend the utility of CBA for the study of the visual system in the context of group analyses. CBA should be particularly relevant when studying neuropsychiatric disorders with abnormally increased interindividual macroanatomical variability.

category: neuroscience


title: Improved correspondence of fMRI visual field localizer data after cortex-based macroanatomical alignment


title: Aging impairs the essential contributions of non-glial progenitors to neurorepair in the dorsal telencephalon of the Killifish N. furzeri

abstract:
The aging central nervous system (CNS) of mammals displays progressive limited regenerative abilities. Recovery after loss of neurons is extremely restricted in the aged brain. Many research models fall short in recapitulating mammalian aging hallmarks or have an impractically long lifespan. We established a traumatic brain injury model in the African turquoise killifish (Nothobranchius furzeri), a regeneration-competent vertebrate model that evolved to naturally age extremely fast. Stab-wound injury of the aged killifish dorsal telencephalon unveils an impaired and incomplete regeneration response when compared to young individuals. Remarkably, killifish brain regeneration is mainly supported by atypical non-glial progenitors, yet their proliferation capacity appears declined with age. We identified a high inflammatory response and glial scarring to also underlie the hampered generation of new neurons in aged fish. These primary results will pave the way for further research to unravel the factor age in relation to neurorepair, and to improve therapeutic strategies to restore the injured and/or diseased aged mammalian CNS.

HighlightsO_LIAging impairs neurorepair in the killifish pallium at multiple stages of the regeneration process
C_LIO_LIAtypical non-glial progenitors support the production of new neurons in the naive and injured dorsal pallium
C_LIO_LIThe impaired regeneration capacity of aged killifish is characterized by a reduced reactive proliferation of these progenitors followed by a decreased generation of newborn neurons that in addition, fail to reach the injury site
C_LIO_LIExcessive inflammation and glial scarring surface as potential brakes on brain repair in the aged killifish pallium
C_LI


title: Comprehensive analysis of chemical and biological problems associated with browning agents used in aquatic studies

abstract:
Inland waters receive and process large amounts of colored organic matter from the terrestrial surroundings. These inputs dramatically affect the chemical, physical, and biological properties of water bodies, as well as their roles as global carbon sinks and sources. To understand the complex changes associated with allochthonous inputs, experiments are needed. However, manipulative studies, especially at ecosystem scales, require large amounts of dissolved organic matter with optical and chemical properties resembling indigenous organic matter. Here we compared the chemical and biological impacts of two leonardite products (HuminFeed (HF) and SuperHume (SH)) and a freshly derived reverse osmosis concentrate of organic matter (RO) in a set of comprehensive mesocosm- and laboratory-scale experiments and analyses.

The chemical properties of RO concentrate and the leonardite products were very different with leonardite products being low and RO being high in carboxylic functional groups. Light had a strong impact on the properties of leonardite products, including loss of color and increased particle formation. Furthermore, HF had drastic impacts on bacteria as light stimulated bacterial production and modified community composition, while dark conditions appeared to inhibit bacterial processes. While none of the browning agents inhibited the growth of the tested phytoplankton, Gonyostomum semen, leonardite products had detrimental effects on zooplankton abundance and Daphnia reproduction. We conclude that the effects of browning agents extracted from leonardite are in sharp contrast to those originating from terrestrially-derived DOM. Hence, they should be used with great caution in experimental studies on the consequences of terrestrial carbon for aquatic systems.


title: High-Throughput Sequencing of 5S-IGS rDNA in Fagus L. (Fagaceae) reveals complex evolutionary patterns and hybrid origin of modern species

abstract:
Standard models of plant speciation assume strictly dichotomous genealogies in which a species, the ancestor, is replaced by two offspring species. The reality in wind-pollinated trees with long evolutionary histories is more complex: species evolve from other species through isolation when genetic drift exceeds gene flow; lineage mixing can give rise to new species (hybrid taxa such as nothospecies and allopolyploids). The multi-copy, potentially multi-locus 5S rDNA is one of few gene regions conserving signal from dichotomous and reticulate evolutionary processes down to the level of intra-genomic recombination. Therefore, it can provide unique insights into the dynamic speciation processes of lineages that diversified tens of millions of years ago. Here, we provide the first high-throughput sequencing (HTS) of the 5S intergenic spacers (5S-IGS) for a lineage of wind-pollinated subtropical to temperate trees, the Fagus crenata - F. sylvatica s.l. lineage, and its distant relative F. japonica. The observed 4,963 unique 5S-IGS variants reflect a complex history of hybrid origins, lineage sorting, mixing via secondary gene flow, and intra-genomic competition between two or more paralogous-homoeologous 5S rDNA lineages. We show that modern species are genetic mosaics and represent a striking case of ongoing reticulate evolution during the past 55 million years.

Significance statementThe evolution of extra-tropical wind-pollinated tree genera involves dynamic speciation processes. High-throughput sequencing of the multi-copy, potentially multi-locus 5S rDNA reveals a complex history of hybrid origins, lineage sorting and mixing, and intra-genomic competition between paralogous-homeologous loci in the core group of Eurasian beech trees (genus Fagus) and their distant relative, F. japonica. The modern species are genetic mosaics and represent a striking case of at least 55 million years of ongoing reticulate evolution.


title: 5S-IGS rDNA in wind-pollinated trees ( Fagus  L.) encapsulates 55 million years of reticulate evolution and hybrid origins of modern species


title: Simulating rhizodeposition patterns around growing and exuding root systems

abstract: 1In this study, we developed a novel model approach to compute the spatio-temporal distribution patterns of rhizodeposits around growing root systems in three dimensions. This model approach allows us for the first time to study the evolution of rhizodeposition patterns around complex three-dimensional root systems. Root systems were generated using the root architecture model CPlantBox. The concentration of rhizodeposits at a given location in the soil domain was computed analytically. To simulate the spread of rhizodeposits in the soil, we considered rhizodeposit release from the roots, rhizodeposit diffusion into the soil, rhizodeposit sorption to soil particles, and rhizodeposit degradation by microorganisms. To demonstrate the capabilities of our new model approach, we performed simulations for the two example rhizodeposits mucilage and cit-rate and the example root system Vicia faba. The rhizodeposition model was parameterized using values from the literature. Our simulations showed that the rhizosphere soil volume with rhizodeposit concentrations above a defined threshold value (i.e., the rhizodeposit hotspot volume), exhibited a maximum at intermediate root growth rates. Root branching allowed the rhizospheres of individual roots to overlap, resulting in a greater volume of rhizodeposit hotspots. This was particularly important in the case of citrate, where overlap of rhizodeposition zones accounted for more than half of the total rhizodeposit hotspot volumes. Coupling a root architecture model with a rhizodeposition model allowed us to get a better understanding of the influence of root architecture as well as rhizodeposit properties on the evolution of the spatio-temporal distribution patterns of rhizodeposits around growing root systems.


title: The Orb6-Sts5 Axis Regulates Stress Granule Formation and Heat Stress Response in Fission Yeast

abstract: The NDR/LATS family kinases are a subclass of the AGC serine/threonine kinases which are important for morphogenesis and cell growth control. Using the model organism Schizosaccharomyces pombe, we previously reported that the NDR/LATS kinase Orb6 phosphorylates the RNA-binding protein (RBP) Sts5 serine 86 residue on its Intrinsically Disordered Domain (IDD). When dephosphorylated, Sts5 forms ribonucleoprotein (RNP) granules that colocalize with processing bodies (P-Bodies) and translationally repress mRNAs important for polarized cell growth. Here we report that Sts5 puncta colocalize with both P-Bodies and stress granules (SG) in response to glucose starvation, as well as heat, oxidative, and hyperosmotic stress. We find that loss of Sts5 decreases the number of stress granules, indicating that Sts5 has a role in promoting stress granule formation. Conversely, inhibition of Orb6 kinase promotes Sts5 aggregation and stress granule formation. In addition, loss of Sts5 decreases cell survival after heat stress, whereas decreasing Orb6 protein levels or including the sts5S86A mutation, which promotes Sts5 aggregation, leads to increased survival. These data indicate that the Orb6-Sts5 axis is not only important for regulation of polarized growth but also for response to environmental stress, as dysregulation of the Orb6-Sts5 axis affects stress granule formation and cell survival.

category: cell biology


title: Bioorthogonal labeling of transmembrane proteins with non-canonical amino acids allows access to masked epitopes in live neurons

abstract: Progress in biological imaging is intrinsically linked to advances in labeling methods. The explosion in the development of high-resolution and super-resolution imaging calls for new approaches to label targets with small probes. These should allow to faithfully report the localization of the target within the imaging resolution - typically nowadays a few nanometers - and allow access to any epitope of the target, in the native cellular and tissue environment. We report here the development of a complete labeling and imaging pipeline using genetic code expansion and non-canonical amino acids in primary neurons that allows to fluorescently label masked epitopes in target transmembrane proteins in live neurons, both in dissociated culture and organotypic brain slices. This allowed us to image the differential localization of two glutamate receptor auxiliary proteins in complex with their partner with a variety of methods including widefield, confocal, and dSTORM super-resolution microscopy.


title: Identification of theTMEM232 gene associated with atopic dermatitis through targeted capture sequencing

abstract:
BACKGROUNDAtopic dermatitis (AD) is a common and complex skin disorder, and the 5q22.1 region had been reported to be associated with AD.

OBJECTIVETo identify the susceptibility gene for AD in the 5q22.1 region by haplotype and targeted capture sequencing.

METHODSThe haplotypes were reconstructed with our previously genotyping data of four SNPs and six deletions from 3055 Chinese Hans AD patients and 4346 controls. The targeted capture sequencing spanning 5q22.1 region was performed in the selected samples. The gene level enrichment analysis was done using loss of function variants.

RESULTSA total of 60 haplotypes were found, and the H15 haplotype had the strongest association with AD (P = 2.72x10 -10, OR = 0.14, 95%CI = 0.07-0.28). However, No co-segregation mutation sites were found in the sequencing analysis within the 16 selected samples, while the enrichment analysis indicated that TMEM232 was significantly associated with AD (P = 7.33x10 -5, OR = 0.33, 95% CI = 0.19-0.58).

CONCLUSIONSThis study confirms previous findings that the TMEM232 gene is associated with AD by haplotype analysis and targeted capture sequencing.


title: Structural basis of substrate recognition and translocation by human ABCA4

abstract: Human ATP-binding cassette (ABC) subfamily A (ABCA) transporters mediate the transport of various lipid compounds across the membrane. Mutations in human ABCA transporters have been described to cause severe hereditary disorders associated with impaired lipid transport. However, little is known about the mechanistic details of substrate recognition and translocation by ABCA transporters. Here, we present three cryo-EM structures of human ABCA4, a retinal-specific ABCA transporter, in distinct functional states at resolutions of 3.3-3.4 [A]. In the nucleotide-free state, the two transmembrane domains (TMDs) exhibited a lateral-opening conformation, allowing the lateral entry of substrate from the lipid bilayer. N-retinylidene-phosphatidylethanolamine (NRPE), the physiological lipid substrate of ABCA4, is sandwiched between the two TMDs in the luminal leaflet and is further stabilized by an extended loop from extracellular domain 1. In the ATP-bound state, the two TMDs displayed an unprecedented closed conformation, which precludes the substrate binding. Our study provides a molecular basis to understand the mechanism of ABCA4-mediated NRPE recognition and translocation, and suggests a common  lateral access and extrusion mechanism for ABCA-mediated lipid transport.

category: biochemistry


title: Bioptim, a Python framework for Musculoskeletal Optimal Control in Biomechanics

abstract: Musculoskeletal simulations are useful in biomechanics to investigate the causes of movement disorder, to estimate non-measurable physiological quantities or to study the optimality of human movement. We introduce Bioptim, an easy-to-use Python framework for biomechanical optimal control, handling musculoskeletal models. Relying on algorithmic differentiation and the multiple shooting formulation, Bioptim interfaces nonlinear solvers to quickly provide dynamically consistent optimal solutions. The software is both computationally efficient (C++ core) and easily customizable, thanks to its Python interface. It allows to quickly define a variety of biomechanical problems such as motion tracking/prediction, muscle-driven simulations, parameters optimization, multiphase problems, etc. It is also intended for real-time applications such as moving horizon estimation and model predictive control. Six contrasting examples are presented, comprising various models, dynamics, objective functions and constraints. They include data-driven simulations (i.e., a multiphase muscle driven gait cycle and an upper-limb real-time moving horizon estimation of muscle forces) and predictive simulations (i.e., a muscle-driven pointing task, a twisting somersault with a quaternion-based model, a position controller using external forces, and a multiphase torque-driven maximum-height jump motion).


title: Representation learning applications in biological sequence analysis

abstract: Remarkable advances in high-throughput sequencing have resulted in rapid data accumulation, and analyzing biological (DNA/RNA/protein) sequences to discover new insights in biology has become more critical and challenging. To tackle this issue, the application of natural language processing (NLP) to biological sequence analysis has received increased attention, because biological sequences are regarded as sentences and k-mers in these sequences as words. Embedding is an essential step in NLP, which converts words into vectors. This transformation is called representation learning and can be applied to biological sequences. Vectorized biological sequences can be used for function and structure estimation, or as inputs for other probabilistic models. Given the importance and growing trend in the application of representation learning in biology, here, we review the existing knowledge in representation learning for biological sequence analysis.


title: DeCiFering the elusive cancer cell fraction in tumor heterogeneity and evolution

abstract:
Most tumors are heterogeneous mixtures of normal cells and cancer cells, with individual cancer cells distinguished by somatic mutations that accumulated during the evolution of the tumor. The fundamental quantity used to measure tumor heterogeneity from somatic single-nucleotide variants (SNVs) is the Cancer Cell Fraction (CCF), or proportion of cancer cells that contain the SNV. However, in tumors containing copy-number aberrations (CNAs) - e.g. most solid tumors - the estimation of CCFs from DNA sequencing data is challenging because a CNA may alter the mutation multiplicity, or number of copies of an SNV. Existing methods to estimate CCFs rely on the restrictive Constant Mutation Multiplicity (CMM) assumption that the mutation multiplicity is constant across all tumor cells containing the mutation. However, the CMM assumption is commonly violated in tumors containing CNAs, and thus CCFs computed under the CMM assumption may yield unrealistic conclusions about tumor heterogeneity and evolution. The CCF also has a second limitation for phylogenetic analysis: the CCF measures the presence of a mutation at the present time, but SNVs may be lost during the evolution of a tumor due to deletions of chromosomal segments. Thus, SNVs that co-occur on the same phylogenetic branch may have different CCFs.

In this work, we address these limitations of the CCF in two ways. First, we show how to compute the CCF of an SNV under a less restrictive and more realistic assumption called the Single Split Copy Number (SSCN) assumption. Second, we introduce a novel statistic, the descendant cell fraction (DCF), that quantifies both the prevalence of an SNV and the past evolutionary history of SNVs under an evolutionary model that allows for mutation losses. That is, SNVs that co-occur on the same phylogenetic branch will have the same DCF. We implement these ideas in an algorithm named DeCiFer. DeCiFer computes the DCFs of SNVs from read counts and copy-number proportions and also infers clusters of mutations that are suitable for phylogenetic analysis. We show that DeCiFer clusters SNVs more accurately than existing methods on simulated data containing mutation losses. We apply DeCiFer to sequencing data from 49 metastatic prostate cancer samples and show that DeCiFer produces more parsimonious and reasonable reconstructions of tumor evolution compared to previous approaches. Thus, DeCiFer enables more accurate quantification of intra-tumor heterogeneity and improves downstream inference of tumor evolution.

Code availabilitySoftware is available at https://github.com/raphael-group/decifer


title: Downsizing in plants - UV induces pronounced morphological changes in cucumber in the absence of stress

abstract: Ultraviolet (UV)-A- or UV-B-enrichment of growth light resulted in a stocky cucumber (Cucumis sativus L.) phenotype exhibiting decreased stem and petiole lengths and leaf area. Effects were larger in plants grown in UV-B- than in UV-A-enriched light. In plants grown in UV-A-enriched light, decreases in stem and petiole lengths were similar independently of tissue age. In the presence of UV-B radiation, stems and petioles were progressively shorter the younger the tissue. Also, plants grown under UV-A-enriched light significantly reallocated photosynthate from shoot to root and also had thicker leaves with decreased specific leaf area. Our data therefore imply different morphological plant regulatory mechanisms under UV-A and UV-B radiation. There was no evidence of stress in the UV-exposed plants, neither in photosynthetic parameters, total chlorophyll content, nor in accumulation of damaged DNA (cyclobutane pyrimidine dimers). The ABA content of the plants also was consistent with non-stress conditions. Parameters such as total leaf antioxidant activity, leaf adaxial epidermal flavonol content and foliar total UV-absorbing pigment levels revealed successful UV acclimation of the plants. Thus, the stocky UV-phenotype was displayed by healthy cucumber plants, implying a strong morphological response and regulatory adjustment as part of UV acclimation processes involving UV-A and/or UV-B photoreceptors.


title: Identification of a chromosomally-encoded sucrose operon-like gene cluster in Vibrio parahaemolyticus strain PH05 isolated from Negros Island, Philippines

abstract: The ability of bacteria to metabolize a wide variety of carbon sources has been known to aid in their ability for efficient colonization. Vibrio parahaemolyticus, a known aquatic pathogen has been reported to have the ability to metabolize a number of carbohydrates including D-glucose, D-galactose, L-arabinose, D-mannose, and D-ribose to name a few. Classical isolation of V. parahaemolyticus from other members of the family Vibrionaceae relies on its carbon utilization pattern. Conventionally, V. parahaemolyticus lacks the ability to utilize sucrose and this has been the basis for its isolation using the Thiosulfate-citrate-bile salts-sucrose (TCBS) agar. Reports of V. parahaemolyticus having the ability to utilize sucrose have been presented yet there is paucity of information and detailed study on this phenotype. In this study, we report the V. parahaemolyticus strain PH05 that has the ability to metabolize sucrose. Phenotypic and genotypic characterization of this V. parahaemolyticus strain isolated from Negros Island, Philippines, revealed that V. parahaemolyticus strain PH05 is atypical appearing yellow on TCBS agar plates. It is capable of utilizing sucrose, unlike the majority of V. parahaemolyticus isolates. Genome analyses of this strain revealed the presence of a chromosomally encoded sucrose operon-like gene cluster encoded in chromosome 2 with the following sucrose-utilization associated genes: scrY, ccpA, treP, scrK, and scrB genes coding for sucrose porin, catabolite control protein A, PTS System sucrose-specific EIIBC component, fructokinase, and sucrose-6-phosphate hydrolase. The mode of transmission of these genes to V. parahaemolyticus strain PH05 is still unknown. However, the presence of insertion sequences (IS) and phage elements in the same chromosome suggests horizontal gene transfer events. Taken together, our results point to the possibility that acquired sucrose utilization genes may contribute to the fitness of V. parahaemolyticus strain PH05 in the environment.

category: microbiology


title: Protection from lethal Clostridioides difficile infection via intraspecies competition for co-germinant

abstract:
Clostridioides difficile, a Gram-positive, spore-forming bacterium, is the primary cause of infectious nosocomial diarrhea. Antibiotics are a major risk factor for C. difficile infection (CDI) as they disrupt the gut microbial community, enabling increased germination of spores and growth of vegetative C. difficile. To date the only single-species bacterial preparation that has demonstrated efficacy in reducing recurrent CDI in humans is non-toxigenic C. difficile. Using multiple infection models we determined that pre-colonization with a less virulent strain is sufficient to protect from challenge with a lethal strain of C. difficile, surprisingly even in the absence of adaptive immunity. Additionally, we showed that protection is dependent on high levels of colonization by the less virulent strain and that it is mediated by exclusion of the invading strain. Our results suggest that reduction of amino acids, specifically glycine following colonization by the first strain of C. difficile is sufficient to decrease germination of the second strain thereby limiting colonization by the lethal strain.

ImportanceAntibiotic-associated colitis is often caused by infection with the bacterium Clostridioides difficile. In this study we found that reduction of the amino acid glycine by pre-colonization with a less virulent strain of C. difficile is sufficient to decrease germination of a second strain. This finding demonstrates that the axis of competition for nutrients can include multiple life stages. This work is important, as it is the first to identify a possible mechanism through which pre-colonization with C. difficile, a current clinical therapy, provides protection from reinfection. Furthermore, our work suggests that targeting nutrients utilized by all life stages could be an improved strategy for bacterial therapeutics that aim to restore colonization resistance in the gut.


title: Amplicon sequence variants artificially split bacterial genomes into separate clusters

abstract: Amplicon sequencing variants (ASVs) have been proposed as an alternative to operational taxonomic units (OTUs) for analyzing microbial communities. ASVs have grown in popularity, in part, because of a desire to reflect a more refined level of taxonomy since they do not cluster sequences based on a distance-based threshold. However, ASVs and the use of overly narrow thresholds to identify OTUs increase the risk of splitting a single genome into separate clusters. To assess this risk, I analyzed the intragenomic variation of 16S rRNA genes from the bacterial genomes represented in a rrn copy number database, which contained 20,427 genomes from 5,972 species. As the number of copies of the 16S rRNA gene increased in a genome, the number of ASVs also increased. There was an average of 0.58 ASVs per copy of the 16S rRNA gene for full length 16S rRNA genes. It was necessary to use a distance threshold of 5.25% to cluster full length ASVs from the same genome into a single OTU with 95% confidence for genomes with 7 copies of the 16S rRNA, such as E. coli. This research highlights the risk of splitting a single bacterial genome into separate clusters when ASVs are used to analyze 16S rRNA gene sequence data. Although there is also a risk of clustering ASVs from different species into the same OTU when using broad distance thresholds, those risks are of less concern than artificially splitting a genome into separate ASVs and OTUs.


title: Novel epitopes of human monoclonal antibodies targeting the influenza virus N1 neuraminidase

abstract:
Influenza virus neuraminidase (NA) targeting antibodies are an independent correlate of protection against infection. Antibodies against the NA act by blocking enzymatic activity, preventing virus release and transmission. As we advance the development of improved influenza virus vaccines that incorporate standard amounts of NA antigen, it is important to identify the antigenic targets of human monoclonal antibodies (mAbs). Additionally, it is important to understand how escape from mAbs changes viral fitness. Here, we describe escape mutants generated by serial passage of A/Netherlands/602/2009 (H1N1) in the presence of human anti-N1 mAbs. We observed escape mutations on the N1 protein around the enzymatic site (S364N, N369T and R430Q) and also detected escape mutations located on the sides and bottom of the NA (N88D, N270D and Q313K/R). We found that a majority of escape mutant viruses had increased fitness in vitro but not in vivo. This work increases our understanding of how human antibody responses target the N1 protein.

ImportanceAs improved influenza virus vaccines are being developed, the influenza virus neuraminidase (NA) is becoming an important new target for immune responses. By identifying novel epitopes of anti-NA antibodies, we can improve vaccine design. Additionally, characterizing changes in viruses containing mutations in these epitopes aids in identifying effects of NA antigenic drift.


title: A de novo paradigm for male infertility

abstract: IntroductionDe novo mutations (DNMs) are known to play a prominent role in sporadic disorders with reduced fitness1. We hypothesize that DNMs play an important role in male infertility and explain a significant fraction of the genetic causes of this understudied disorder. To test this hypothesis, we performed trio-based exome-sequencing in a unique cohort of 185 infertile males and their unaffected parents. Following a systematic analysis, 29 of 145 rare protein altering DNMs were classified as possibly causative of the male infertility phenotype. We observed a significant enrichment of Loss-of-Function (LoF) DNMs in LoF-intolerant genes (p-value=1.00x10-5) as well as predicted pathogenic missense DNMs in missense-intolerant genes (p-value=5.01x10-4). One DNM gene identified, RBM5, is an essential regulator of male germ cell pre-mRNA splicing2. In a follow-up study, 5 rare pathogenic missense mutations affecting this gene were observed in a cohort of 2,279 infertile patients, with no such mutations found in a cohort of 5,784 fertile men (p-value=0.009). Our results provide the first evidence for the role of DNMs in severe male infertility and point to many new candidate genes affecting fertility.

category: genetics


title: Chromatin and transcriptomic profiling uncover dysregulation of the Tip60 HAT/HDAC2 epigenomic landscape in the neurodegenerative brain

abstract: Disruption of histone acetylation mediated gene control is a critical step in Alzheimers Disease (AD), yet chromatin analysis of antagonistic histone acetyltransferases (HATs) and histone deacetylases (HDACs) causing these alterations remains uncharacterized. We report the first Tip60 HAT versus HDAC2 chromatin and transcriptional profiling study in Drosophila brains that model early human AD. We find Tip60 and HDAC2 predominantly recruited to identical neuronal genes. Moreover, AD brains exhibit robust genome-wide early alterations that include enhanced HDAC2 and reduced Tip60 binding and transcriptional dysregulation. Orthologous human genes to co-Tip60/HDAC2 Drosophila neural targets exhibit conserved disruption patterns in AD patient hippocampi. Notably, we discovered distinct transcription factor (TF) binding sites within Tip60/HDAC2 co-peaks in neuronal genes, implicating them in co-enzyme recruitment. Increased Tip60 protects against transcriptional dysregulation and enhanced HDAC2 enrichment genome-wide. We advocate Tip60 HAT/HDAC2 mediated epigenetic neuronal gene disruption as a genome-wide initial causal event in AD.


title: Circulating miRNAs associated with bone mineral density in healthy adult baboons.

abstract: MicroRNAs (miRNAs) regulate gene expression post-transcriptionally and circulate in the blood, making them attractive biomarkers of disease state for tissues like bone that are challenging to interrogate directly. Here we report on five miRNAs - miR-197-3p, miR-320a, miR-320b, miR-331-5p, and miR-423-5p - that are associated with bone mineral density (BMD) in 147 healthy adult baboons. These baboons range in age from 15 to 25 years (45 to 75 human equivalent years) and were 65% female with a broad range of BMDs including a minority of osteopenic individuals. miRNAs were generated via RNA sequencing from buffy coats collected at necropsy and areal BMD evaluated via DXA of the lumbar vertebrae post-mortem. Differential expression analysis controlled for the underlying pedigree structure of these animals to account for genetic variation which may be driving miRNA abundance and BMD values. While many of these miRNAs have been associated with risk of human osteoporosis, this finding is of interest because the cohort represent a model of normal aging and bone metabolism rather than a disease cohort. The replication of miRNA associations with osteoporosis or other bone metabolic disorders in animals with healthy BMD suggests an overlap in normal variation and disease states. We suggest that these miRNAs are involved in the regulation of cellular proliferation, apoptosis, and protein composition in the extracellular matrix throughout life. However, age-related dysregulation of these systems may lead to disease causing associations of the miRNAs among individuals with clinically defined disease.


title: APOBEC Mutagenesis is Concordant Between Tumor and Viral Genomes in HPV Positive Head and Neck Squamous Cell Carcinoma

abstract: APOBEC (apolipoprotein B mRNA-editing enzyme, catalytic polypeptide-like) is a major mutagenic source in human papillomavirus positive oropharyngeal squamous cell carcinoma (HPV+ OPSCC). Why APOBEC mutations predominate in HPV+OPSCC remains an area of active investigation. Prevailing theories focus on APOBECs role as a viral restriction agent. APOBEC-induced mutations have been identified in both human cancers and HPV genomes, but whether they are directly linked in HPV+OPSCCs remains unknown. We performed sequencing of host somatic exomes, transcriptomes and HPV16 genomes from 79 HPV+ OPSCC samples, quantifying APOBEC mutational burden and activity in both the host and virus. APOBEC was the dominant mutational signature in somatic exomes. APOBEC vulnerable PIK3CA hotspot mutations were exclusively present in APOBEC enriched samples. In viral genomes, there was a mean (range) of 5 (0-29) mutations per genome. Mean (range) of APOBEC mutations in the viral genomes was 1 (0-5). Viral APOBEC mutations, compared to non-APOBEC mutations, were more likely to be low-variant allele frequency mutations, suggesting that APOBEC mutagenesis is actively occurring in viral genomes during infection. Paired host and viral analyses revealed that APOBEC-enriched tumor samples had higher viral APOBEC mutation rates (p=0.028), and APOBEC-associated RNA editing (p=0.008) suggesting that APOBEC mutagenesis in host and viral genomes are directly linked. Using paired sequencing of host somatic exomes, transcriptomes, and viral genomes from HPV+OPSCC samples, here, we show concordance between tumor and viral APOBEC mutagenesis, suggesting that APOBEC-mediated viral restriction results in off-target host-genome mutations. These data provide a missing link connecting APOBEC mutagenesis in host and virus and support a common mechanism driving APOBEC dysregulation.


title: Structural basis of phosphorylation kinetics in the transcriptional activation domain (TAD) of c-Jun and insight of two new phosphorylation sites Ser58 and Thr62

abstract: This manuscript has been removed due to unethical behavior by the authors that includes violation of copyright.


title: Murine norovirus capsid plasticity - Glycochenodeoxycholic acid stabilizes P domain dimers and triggers escape from antibody recognition

abstract:
The murine norovirus (MNV) capsid protein is the target for various neutralizing antibodies binding to distal tips of its protruding (P)-domain. The bile acid glycochenodeoxycholic acid (GCDCA), an important co-factor for murine norovirus (MNV) infection, has recently been shown to induce conformational changes in surface-loops and a contraction of the virion. Here, we employ protein NMR experiments using stable isotope labeled MNV P-domains to shed light on underlying molecular mechanisms. We observe two separate sets of NMR resonance signals for P-domain monomers and dimers, permitting analysis of the corresponding exchange kinetics. Unlike human norovirus GII.4 P-dimers, which exhibit a half-life in the range of several days, MNV P-dimers are very short lived with a half-life of about 17 s. Addition of GCDCA shifts the equilibrium towards the dimeric form by tightly binding to the P-dimers. In MNV virions GCDCA-mediated stabilization of the dimeric arrangement of P-domains generates a more ordered state, which in turn may entropically assist capsid contraction. Numerous long-range chemical shift perturbations (CSPs) upon addition of GCDCA reflect allosteric conformational changes as a feature accompanying dimer stabilization. In particular, CSPs indicate rearrangement of the EF loop, a target for various neutralizing antibodies. Indeed, treating MNV virions with GCDCA prior to neutralizing antibody exposure abolishes neutralization. These findings advance our understanding of GCDCA-induced structural changes of MNV capsids and experimentally support an intriguing viral immune escape mechanism relying on GCDCA-triggered conformational changes of the P-dimer.

Significance StatementThis study sheds light on the role of glycochenodeoxycholic acid (GCDCA) in promoting murine norovirus (MNV) infection and immune escape. Binding of GCDCA to the dimeric P-domain has been well characterized by crystallography and cryo EM studies, showing that upon GCDCA binding, a 90{degrees} rotation of the P-domain occurs, which results in its collapse onto the underlying shell of the virus. Our NMR experiments now reveal P-dimer stability as a new dimension of plasticity of MNV capsids and suggest that capsid contraction is entropically assisted. Conformational changes as a feature of P-dimer stabilization eliminate recognition by neutralizing antibodies, no longer being able to prevent infection. These findings highlight key differences between human and MNV capsid structures, promote our understanding of MNV infection on a molecular level, and reveal a novel immune escape mechanism.


title: Quantitative consequences of protein carriers in immunopeptidomics and tyrosine phosphorylation MS2 analyses

abstract: Utilizing a protein carrier in combination with isobaric labeling to "boost" the signal of other low-level samples in multiplexed analyses has emerged as an attractive strategy to enhance data quantity while minimizing protein input in mass spectrometry analyses. Recent applications of this approach include pMHC profiling and tyrosine phosphoproteomics, two applications that are often limited by large sample requirements. While including a protein carrier has been shown to increase the number of identifiable peptides in both applications, the impact of a protein carrier on quantitative accuracy remains to be thoroughly explored, particularly in relevant biological contexts where samples exhibit dynamic changes in abundance across peptides. Here, we describe two sets of analyses comparing MS2-based quantitation using a 20x protein carrier in pMHC analyses and a high ([~]100x) and low ([~]9x) protein carrier in pTyr analyses, using CDK4/6 inhibitors and EGF stimulation to drive dynamic changes in the immunopeptidome and phosphoproteome, respectively. In both applications, inclusion of a protein carrier resulted in an increased number of MHC peptide or phosphopeptide identifications, as expected. At the same time, quantitative accuracy was adversely affected by the presence of the protein carrier, altering interpretation of the underlying biological response to perturbation. Moreover, for tyrosine phosphoproteomics, the presence of high levels of protein carrier led to a large number of missing values for endogenous phosphopeptides, leading to fewer quantifiable peptides relative to the "no-boost" condition. These data highlight the unique limitations and future experimental considerations for both analysis types and provide a framework for assessing quantitative accuracy in protein carrier experiments moving forward.


title: Fiber density and matrix stiffness modulate distinct cell migration modes in a 3D stroma mimetic composite hydrogel

abstract: The peritumoral stroma is a complex 3D tissue that provides cells with myriad biophysical and biochemical cues. Histologic observations suggest that during metastatic spread of carcinomas, these cues influence transformed epithelial cells, prompting a diversity of migration modes spanning single cell and multicellular phenotypes. Purported consequences of these variations in tumor escape strategies include differential metastatic capability and therapy resistance. Therefore, understanding how cues from the peritumoral stromal microenvironment regulate migration mode phenotypes has prognostic and therapeutic value. Here, we utilize a synthetic stromal mimetic in which matrix fiber density and bulk hydrogel stiffness can be orthogonally tuned to investigate the contribution of these two key matrix attributes on MCF10A migration mode phenotypes, epithelial-mesenchymal transition (EMT), and invasive potential. We developed an automated computational image analysis framework to extract migratory phenotypes from fluorescent images and determine 3D migration metrics relevant to metastatic spread. Using this analysis, we find that matrix fiber density and bulk hydrogel stiffness distinctly contribute to a variety of MCF10A migration modes including amoeboid, single mesenchymal, multicellular clusters, and collective strands. Taking advantage of the tunability of this material platform, we identify a combination of physical and soluble cues that induces distinct heterogeneous migration modes originating from the same MCF10A spheroid and use this setting to examine a functional consequence of migration mode - apoptotic resistance. We find that cells migrating as part of collective strands are more resistant to staurosporine-induced apoptosis than either disconnected multicellular clusters or individual invading cells. Improved models of the peritumoral stromal microenvironment that help elucidate relationships between matrix attributes and cell migration mode can contribute to ongoing efforts to identify efficacious cancer therapeutics that address migration plasticity-based therapy resistances.


title: Discovering single nucleotide variants and indels from bulk and single-cell ATAC-seq

abstract: Genetic variants and de novo mutations in regulatory regions of the genome are typically discovered by whole-genome sequencing (WGS), however WGS is expensive and most WGS reads come from non-regulatory regions. The Assay for Transposase-Accessible Chromatin (ATAC-seq) generates reads from regulatory sequences and could potentially be used as a low-cost  capture method for regulatory variant discovery, but its use for this purpose has not been systematically evaluated. Here we apply seven variant callers to bulk and single-cell ATAC-seq data and evaluate their ability to identify single nucleotide variants (SNVs) and insertions/deletions (indels). In addition, we develop an ensemble classifier, VarCA, which combines features from individual variant callers to predict variants. The Genome Analysis Toolkit (GATK) is the best-performing individual caller with precision/recall on a bulk ATAC test dataset of 0.92/0.97 for SNVs and 0.87/0.82 for indels. On bulk ATAC-seq reads, VarCA achieves superior performance with precision/recall of 0.99/0.95 for SNVs and 0.93/0.80 for indels. On single-cell ATAC-seq reads, VarCA attains precision/recall of 0.98/0.94 for SNVs and 0.82/0.82 for indels. In summary, ATAC-seq reads can be used to accurately discover non-coding regulatory variants in the absence of whole-genome sequencing data and our ensemble method, VarCA, has the best overall performance.


title: Hyperspectral sensing of photosynthesis, stomatal conductance, and transpiration for citrus tree under drought condition

abstract:
Obtaining variation in water use and photosynthetic capacity is a promising route toward yield increases, but it is still too laborious for large-scale rapid monitoring and prediction. We tested the application of hyperspectral reflectance as a high-throughput phenotyping approach for early identification of water stress and rapid assessment of leaf photosynthetic traits in citrus trees. To this end, photosynthetic CO2 assimilation rate (Pn), stomatal conductance (Cond) and transpiration rate (Trmmol) were measured with gas-exchange approaches alongside measurements of leaf hyperspectral reflectance from citrus grown across a gradient of soil drought levels. Water stress caused Pn, Cond and Trmmol rapid and continuous decreases in whole drought period. Upper layer was more sensitive to drought than middle and lower layers. Original reflectance spectra of three drought treatments were surprisingly of low diversity and could not track drought responses, whereas specific hyperspectral spectral vegetation indices (SVIs) and absorption features or wavelength position variables presented great potential. Performance of four machine learning algorithms were assessed and random forest (RF) algorithm yielded the highest predictive power for predicting photosynthetic parameters. Our results indicated that leaf hyperspectral reflectance was a reliable and stable method for monitoring water stress and yield increasing in large-scale orchards.

HighlightAn efficient and stable methods using hyperspectral features for early and pre-visual identification of drought and machine learning techniques for predicting photosynthetic capacity.

category: physiology


title: Programmatic modeling for biological systems

abstract:
Computational modeling has become an established technique to encode mathematical representations of cellular processes and gain mechanistic insights that drive testable predictions. These models are often constructed using graphical user interfaces or domain-specific languages, with SBML used for interchange. Models are typically simulated, calibrated, and analyzed either within a single application, or using import and export from various tools. Here, we describe a programmatic modeling paradigm, in which modeling is augmented with best practices from software engineering. We focus on Python - a popular, user-friendly programming language with a large scientific package ecosystem. Models themselves can be encoded as programs, adding benefits such as modularity, testing, and automated documentation generators while still being exportable to SBML. Automated version control and testing ensures models and their modules have expected properties and behavior. Programmatic modeling is a key technology to enable collaborative model development and enhance dissemination, transparency, and reproducibility.

HighlightsO_LIProgrammatic modeling combines computational modeling with software engineering best practices.
C_LIO_LIAn executable model enables users to leverage all available resources from the language.
C_LIO_LICommunity benefits include improved collaboration, reusability, and reproducibility.
C_LIO_LIPython has multiple modeling frameworks with a broad, active scientific ecosystem.
C_LI


title: A unicellular walker embodies a finite state machine

abstract:
Cells are complex biochemical systems whose behavior emerges from interactions among myriad molecular components. Computation is often invoked as a general framework for navigating this cellular complexity. However, the manner in which cells might embody computational processes such that theories of computation, including finite state machine models, could be productively applied, remains to be seen. Here we demonstrate finite state machine-like processing embodied in cells using the walking behavior of Euplotes eurystomus, a ciliate that walks across surfaces using fourteen motile appendages (cirri). We found that cellular walking entails highly regulated transitions between a discrete set of gait states. The set of observed transitions decomposes into a small group of high-probability, temporally irreversible transitions forming a cycle and a large group of low-probability time-symmetric transitions, thus revealing stereotypy in sequential patterns of state transitions. Taken together, these findings implicate a finite state machine-like process. Cirri are connected by microtubule bundles, and we found that the dynamics of cirri involved in different state transitions are associated with the structure of the microtubule bundle system. Perturbative experiments revealed that the fibers mediate gait coordination, suggesting a mechanical basis of gait control.

One sentence summaryThe ciliate Euplotes walks across surfaces with an unusual gait, which involves modular subcellular structure and combines elements of stereotypy and variability according to a computational process actively coordinated by a microtubule fiber system.


title: A unicellular walker controlled by a microtubule-based finite state machine


title: Single-cell analysis identifies a key role for Hhip in murine coronal suture development

abstract: Craniofacial development depends on proper formation and maintenance of sutures between adjacent bones of the skull. In sutures, bone growth occurs at the edge of each bone, and suture mesenchyme maintains the separation between them. We performed single-cell RNA-seq analyses of the embryonic, murine coronal suture. Analyzing replicate libraries at E16.5 and E18.5, we identified 14 cell populations. Seven populations at E16.5 and nine at E18.5 comprised the suture mesenchyme, osteogenic cells, and associated populations. Through an integrated analysis with bulk RNA-seq data, we found a distinct coronal suture mesenchyme population compared to other neurocranial sutures, marked by expression of Hhip, an inhibitor of hedgehog signaling. We found that at E18.5, Hhip-/- coronal osteogenic fronts are closely apposed and suture mesenchyme is depleted, demonstrating that Hhip is required for coronal suture development. Our transcriptomic approach provides a rich resource for insight into normal and abnormal development.

category: developmental biology


title: Cascading indirect genetic effects in a clonal vertebrate

abstract: Understanding how individual differences among organisms arise and how their effects propagate through groups of interacting individuals are fundamental questions in biology.Individual differences can arise from genetically-based variation in the conspecifics with which an individual interacts, and these effects might then be propagated to other individuals. Using a clonal species, the Amazon molly (Poecilia formosa), we test the hypothesis that such indirect genetic effects (IGE) propagate beyond individuals that experience them firsthand. We tested this hypothesis by exposing genetically identical Amazon mollies to social partners of different genotypes, and then moving these individuals to new social groups in which they were the only member to have experienced the IGE. We found that genetically different social environments induced different levels of aggression experienced by the focal animals, and that these genetically-based social effects carried over into new social groups to influence the behavior of individuals that did not directly experience the previous social environments. Our data reveal that IGE can cascade beyond the individuals that directly experience them to influence phenotypes even when there is no genetically-based variation present within interacting groups. Theoretical and empirical expansion of the quantitative genetic framework developed for IGE to include cascading and other types of carry-over effects will improve understanding of social behavior and its evolution.

category: animal behavior and cognition