Biology subjects

He, Z.

Publications and source records attributed to He, Z..

At least 253 records · Page 14Linked to original sources

bioRxiv2020

Trantrace: a reliable, traceable, and collaborative solution to streamline the translation of emerging biomedical resources

BackgroundPrecision medicine is gaining popularity in routine health care, which heavily relies on the interpretation of emerging biomedical databases and professional guidelines. Translation of those biomedical materials, that is crucial to deliver research discovery to health interventions in non-native English-speaking countries, remains a large amount of work for biomedical practitioners. ResultsWe presented an application called Trantrace to facilitate the routine of large-scale long-running translation. Especially for the case that many people joined multiple translation projects, it has a rigorous task division and cooperation process: assignment, translation, review, release, and iteration. Trantrace empowers users to build own projects with different permissions, version control all the translation operation without specific skills, and further improve the translation efficiency through real-time task management tools. ConclusionsBy providing a working platform for collaborative translation and enabling long-time version correction, the Trantrace contributes towards the creation of a multilingual biomedical knowledge commons, which would be a valuable aid for personalized therapies. The source code is freely accessible at https://github.com/sgi-drylab/trantrace.

bioinformatics↗

bioRxiv2020

Multitrait genetic-phenotype associations to connect disease variants and biological mechanisms

BackgroundGenome-wide association studies (GWAS) uncovered a wealth of associations between common variants and human phenotypes. These results, widely shared across the scientific community as summary statistics, fostered a flurry of secondary analysis: heritability and genetic correlation assessment, pleiotropy characterization and multitrait association test. Amongst these secondary analyses, a rising new field is the decomposition of multitrait genetic effects into distinct profiles of pleiotropy. ResultsWe conducted an integrative analysis of GWAS summary statistics from 36 phenotypes to decipher multitrait genetic architecture and its link to biological mechanisms. We started by benchmarking multitrait association tests on a large panel of phenotype sets and established the Omnibus test as the most powerful in practice. We detected 322 new associations that were not previously reported by univariate screening. Using independent significant associations, we investigated the breakdown of genetic association into clusters of variants harboring similar multitrait association profile. Focusing on two subsets of immunity and metabolism phenotypes, we then demonstrate how SNPs within clusters can be mapped to biological pathways and disease mechanisms, providing a putative insight for numerous SNPs with unknown biological function. Finally, for the metabolism set, we investigate the link between gene cluster assignment and success of drug targets in random control trials. We report additional uninvestigated drug targets classified by clusters. ConclusionsMultitrait genetic signals can be decomposed into distinct pleiotropy profiles that reveal consistent with pathways databases and random control trials. We propose this method for the mapping of unannotated SNPs to putative pathways.

genetics↗

bioRxiv2020

Development of a whole cell biosensor for detection of 2, 4-diacetylphloroglucinol (DAPG) producing bacteria from grassland soil

Fluorescent Pseudomonas spp. producing the antibiotic 2,4-diacetylphloroglucinol (DAPG) are ecologically important in the rhizosphere as they can control phytopathogens and contribute to disease suppressiveness. While studies of DAPG-producing Pseudomonas have predominantly focused on rhizosphere niches, the ecological role of DAPG as well as the distribution and dynamics of DAPG-producing bacteria remains less well understood for other environments such as bulk soil and grassland, where the level of DAPG producers are predicted to be low. Here, we construct a whole cell biosensor for detection of DAPG and DAPG-producing bacteria from environmental samples. We show that the sensor is highly specific towards DAPG, with a sensitivity in the low nanomolar range (<20 nm). This sensitivity is comparable to the DAPG levels identified in rhizosphere samples by chemical analysis. The biosensor enables guided isolation of DAPG-producing Pseudomonas. Using the biosensor, we probed the same grassland soil sampling site to isolate genetically related DAPG-producing Pseudomonas kilonensis strains over a period of 12 months. Next, we used the biosensor to determine the frequency of DAPG-producing Pseudomonads within three different grassland soil sites and show that DAPG producers can constitute part of the Pseudomonas population in the range of 0.35-17% at these sites. Finally, we show that the biosensor enables detection of DAPG produced by non-Pseudomonas species. Our studies show that a whole-cell biosensor for DAPG detection can facilitate isolation of bacteria that produce this important secondary metabolite and provide insight into the population dynamics of DAPG producers in natural grassland soil. IMPORTANCEThe interest has grown for bacterial biocontrol agents as biosustainable alternatives to pesticides to increase crop yields. Currently, we have a broad knowledge of antimicrobial compounds, such as DAPG, produced by bacteria growing in the rhizosphere surrounding plant roots. However, compared to the rhizosphere niches, the ecological role of DAPG as well as the distribution and dynamics of DAPG-producing bacteria remains less well understood for other environments such as bulk and grassland soil. Currently, we are restricted to chemical methods with detection limits and time-consuming PCR-based and probe-hybridization approaches to detect DAPG and its respective producer. In this study, we have developed a whole-cell biosensor, which can circumvent the labor-intensive screening process, as well as increase the sensitivity at which DAPG is detected. This enables quantification of relative amounts of DAPG-producers, which in turn increases our understanding of the dynamics and ecology of these producers in natural soil environments.

microbiology↗

bioRxiv2020

Lineage recording reveals dynamics of cerebral organoid regionalization

Diverse regions develop within cerebral organoids generated from human induced pluripotent stem cells (iPSCs), however it has been a challenge to understand the lineage dynamics associated with brain regionalization. Here we establish an inducible lineage recording system that couples reporter barcodes, inducible CRISPR/Cas9 scarring, and single-cell transcriptomics to analyze lineage relationships during cerebral organoid development. We infer fate-mapped whole organoid phylogenies over a scarring time course, and reconstruct progenitor-neuron lineage trees within microdissected cerebral organoid regions. We observe increased fate restriction over time, and find that iPSC clones used to initiate organoids tend to accumulate in distinct brain regions. We use lineage-coupled spatial transcriptomics to resolve lineage locations as well as confirm clonal enrichment in distinctly patterned brain regions. Using long term 4-D light sheet microscopy to temporally track nuclei in developing cerebral organoids, we link brain region clone enrichment to positions in the neuroectoderm, followed by local proliferation with limited migration during neuroepithelial formation. Our data sheds light on how lineages are established during brain organoid regionalization, and our techniques can be adapted in any iPSC-derived cell culture system to dissect lineage alterations during perturbation or in patient-specific models of disease.Competing Interest StatementThe authors have declared no competing interest.View Full Text

developmental biology↗

bioRxiv2020

Fractalkine-induced microglial vasoregulation occurs within the retina and is altered early in diabetic retinopathy

Local blood flow control within the CNS is critical to proper function and is dependent on coordination between neurons, glia and blood vessels. Macroglia such as astrocytes and Muller cells, contribute to this neurovascular unit within the brain and retina, respectively. This study explored the role of microglia, the innate immune cell of the CNS, in retinal vasoregulation and highlights changes during early diabetes. Structurally, microglia were found to contact retinal capillaries and neuronal synapses. In the brain and retinal explants, the addition of fractalkine, the sole ligand for monocyte receptor Cx3cr1, resulted in capillary constriction at regions of microglial contact. This vascular regulation was dependent on microglial involvement, since mice lacking Cx3cr1, exhibited no fractalkine-induced constriction. Analysis of the microglial transcriptome identified several vasoactive genes, including angiotensinogen, a constituent of the renin-angiotensin system (RAS). Subsequent functional analysis showed that RAS blockade via candesartan, abolished microglial-induced capillary constriction. Microglial regulation was explored in a rat streptozotocin (STZ) model of diabetic retinopathy. Retinal blood flow was reduced after 4 weeks due to reduced capillary diameter and this was coincident with increased microglial association. Functional assessment showed loss of microglial-capillary response in STZ-treated animals and transcriptome analysis showed evidence of RAS pathway dysregulation in microglia. While candesartan treatment reversed capillary constriction in STZ-treated animals, blood flow remained decreased likely due to dilation of larger vessels. This work shows microglia actively participate in the neurovascular unit, with aberrant microglial-vascular function possibly contributing to the early vascular compromise during diabetic retinopathy. Significance StatementThis work identifies a novel role for microglia, the innate immune cells of the CNS, in the local control of the retinal vasculature and identifies deficits early in diabetes. Microglia contact neurons and vasculature and express several vasoactive agents. Activation of microglial fractalkine-Cx3cr1 signalling leads to capillary constriction and blocking the renin-angiotensin system (RAS) with candesartan abolishes microglial-mediated vasoconstriction in the retina. In early diabetes, reduced retinal blood flow is coincident with capillary constriction, increased microglial-vessel association, loss of microglial-capillary regulation and altered microglial expression of the RAS pathway. While candesartan restores retinal capillary diameter early in diabetes, targeting of microglial-vascular regulation is required to prevent coincident dilation of large retinal vessels and reduced retinal blood flow.

cell biology↗

bioRxiv2020

Molecules inhibit the enzyme activity of 3-chymotrypsin-like cysteine protease of SARS-CoV-2 virus

SARS-CoV-2 has emerged as a world public health threat. Herein, we report that the clinical approved auranofin could perfectly inhibit the activity of 3-chymotrypsin-like cysteine protease (Mpro or 3CLpro) of SARS-CoV-2. Gold cluster could significantly inhibit 3CLpro of SARS-COV-2. Phenyl isothiocyanate and Vitamin K3 could well suppress the activity of 3CLpro. For Mpro inhibition, IC50 of auranofin, Vitamin K3, phenyl isothiocyanate, gold cluster are about 0.51M, 7.96M, 10.13M, 1.61M, respectively. These compounds may be with potentials for treatment SARS-CoV-2 virus replication. Especially for FDA approved auranofin, it is an anti-inflammation drug in clinic, thus it may with strong potential to inhibit virus replication and suppress the inflammation damage in COVID-19 patients. Gold cluster is with better safety index and well anti-inflammation in vitro/vivo, therefore it is with potential to inhibit virus replication and suppress the inflammation damage caused by COVID-19 virus. As Au(I) ion is active metabolism specie derived from gold compounds or gold clusters in vivo, further computational studies revealed Au ion could tightly bind thiol group of Cys145 residue of 3CLpro thus inhibit enzyme activity. Also, phenyl isothiocyanate and Vitamin K3 may interact with thiol group of Cys145 via Michael addition reaction, molecular dynamic (MD) theory studied are applied to confirmed these small molecules are stable in the pocket and inhibit Mpro activity.

biochemistry↗

bioRxiv2020

Latrophilin-2 repels Teneurin-3+ hippocampal axons during target selection

Parallel information processing is a salient feature of complex nervous systems. For example, the medial and lateral hippocampal networks (MHN and LHN) preferentially process spatial- and object-related information, respectively. However, the mechanisms underlying parallel network assembly during development remain largely unknown. Here, we show that complementary expression of cell-surface molecules Teneurin-3 (Ten3) and Latrophilin-2 (Lphn2) in the MHN and LHN, respectively, guides the precise assembly of both the MHN and LHN. Viral-genetic perturbations in vivo demonstrate that Ten3+ axons are repelled by target-derived Lphn2, revealing that Lphn2/Ten3-mediated repulsion and Ten3/Ten3-mediated attraction cooperate to control precise target selection of MHN axons. In the LHN, Lphn2+ axons are confined to Lphn2+ targets via repulsion from Ten3+ targets. Our findings demonstrate that assembly of parallel hippocampal networks follows a Ten3[->]Ten3, Lphn2[->]Lphn2 rule instructed by reciprocal repulsions.

neuroscience↗

bioRxiv2020

A High Accurate Machine Learning Meta-Strategy for the Prediction of Intrinsically Disorder Proteins

BackgroundMany proteins or partial regions of proteins do not have stable and well-defined three-dimensional structures in vitro. Understanding intrinsically disorder proteins (IDPs) is significant for interpreting biological function as well as studying many diseases. Although more than 70 disorder predictors have been invented, many existing predictors are limited on the characteristics of proteins and do not have very high accuracy. Therefore, it is critical to formulate new strategies on disorder protein prediction. ResultsHere, we propose a machine learning meta-strategy to improve the accuracy of disordered proteins and disordered regions prediction. We first use logistic forward parameter selection to select eight most significant predictors from the current available IDP predictors. Then we design a novel meta-strategy using several machine learning models, including Decision-tree based algorithm, Naive Bayes, Random forest, and Convolutional Neural Network (CNN). By applying different strategies, the results suggest Random forest can improve the predicted single amino acid accuracy significantly to 93.35%. Using the combination vector data of eight most significant predictors as input, the Convolution Neural Network can improve the whole protein prediction to 95.62%. ConclusionAccording to the performance of our machine learning meta-strategy, the Random forest and CNN models can improve the accuracy to predict intrinsically disorder proteins.

bioinformatics↗

bioRxiv2020

Revisiting neoantigen depletion signal in the untreated cancer genome

This study is arising from Van den Eynden J. et al. Nature Genetics. Lack of detectable neoantigen depletion signals in the untreated cancer genome. Van den Eynden J. et al. tried to address a very important scientific question: could the immune system eliminate cancer cells with immunogenic mutations in untreated situation? Van den Eynden J. et al. first annotated the human exome into "HLA-binding regions" and "non HLA-binding regions" based on the predicted binding affinity of nonapeptides translated from the un-mutated reference coding genome with type I HLA alleles. They hypothesized that if neoantigen depletion signal exist, the nonsynonymous mutations in "HLA-binding regions" will be negatively selected during cancer evolution, while nonsynonymous mutation in "non HLA-binding regions" will not be negatively selected. This will lead to decreased nonsynonymous vs synonymous mutation ratio (n/s) in "HLA-binding regions" compared with "non HLA-binding regions". They defined HLA-binding mutation ratio (HBMR) as the ratio of n/s in "HLA-binding regions" to "non HLA-binding regions", and reported that HBMRs are close to 1 in different types of cancer after background corrections, meaning neoantigen depletion signals are not detectable in different types of cancer. The fundamental problem of their hypothesis lies in that the actual neoantigens with immunogenicity do not overlap with their defined "HLA-binding regions". Actually, most neoantigens with immunogenicity are not located in "HLA-binding regions", when dissimilarity between mutant and wild type peptide are considered. It is the neoantigen with immunogenicity, but not nonsynonymous mutation in their defined "HLA-binding regions" undergo immunoediting based negative selection. Thus the results reported in that study are fundamentally flawed, and at this current stage we could not draw a solid conclusion as to whether the neoantigen depletion signal exists or not.

genomics↗

bioRxiv2020

Two decades of suspect evidence for adaptive DNA-sequence evolution - Less negative selection misconstrued as positive selection

Evidence for biological adaptation is often obtained by studying DNA sequence evolution. Since the analyses are affected by both positive and negative selection, studies usually assume constant negative selection in the time span of interest. For this reason, hundreds of studies that conclude adaptive evolution might have reported false signals caused by relaxed negative selection. We test this suspicion two ways. First, we analyze the fluctuation in population size, N, during evolution. For example, the evolutionary rate in the primate phylogeny could vary by as much as 2000 fold due to the variation in N alone. Second, we measure the variation in negative selection directly by analyzing the polymorphism data from four taxa (Drosophila, Arabidopsis, primates, and birds, with 64 species in total). The strength of negative selection, as measured by the ratio of nonsynonymous/synonymous polymorphisms, fluctuates strongly and at multiple time scales. The two approaches suggest that the variation in the strength of negative selection may be responsible for the bulk of the reported adaptive genome evolution in the last two decades. This study corroborates the recent report1 on the inconsistent patterns of adaptive genome evolution. Finally, we discuss the path forward in detecting adaptive sequence evolution.

evolutionary biology↗

bioRxiv2020

sureLDA: A Multi-Disease Automated Phenotyping Method for the Electronic Health Record

ObjectiveA major bottleneck hindering utilization of electronic health record (EHR) data for translational research is the lack of precise phenotype labels. Chart review as well as rule-based and supervised phenotyping approaches require laborious expert input, hampering applicability to studies that require many phenotypes to be defined and labeled de novo. Though ICD codes are often used as surrogates for true labels in this setting, these sometimes suffer from poor specificity. We propose a fully automated topic modeling algorithm to simultaneously annotate multiple phenotypes. MethodssureLDA is a label-free multidimensional phenotyping method. It first uses the PheNorm algorithm to initialize probabilities based on two surrogate features for each target phenotype, and then leverages these probabilities to constrain the Latent Dirichlet Allocation (LDA) topic model to generate phenotype-specific topics. Finally, it combines phenotype-feature counts with surrogates via clustering ensemble to yield final phenotype probabilities. ResultssureLDA achieves reliably high accuracy and precision across a range of simulated and real-world phenotypes. Its performance is robust to phenotype prevalence and relative informativeness of surogate versus non-surrogate features. It also exhibits powerful feature selection properties. DiscussionsureLDA combines attractive properties of PheNorm and LDA to achieve high accuracy and precision robust to diverse phenotype characteristics. It offers particular improvement for phenotypes insufficiently captured by a few surrogate features. Moreover, sureLDAs feature selection ability enables it to handle high feature dimensions and produce interpretable computational phenotypes. ConclusionsureLDA is well suited toward large-scale EHR phenotyping for highly multi-phenotype applications such as PheWAS.

bioinformatics↗

bioRxiv2020

Ursolic acid inhibits cell migration and promotes JNK-dependent lysosomal associated cell death in Glioblastoma multiforme cells

Ursolic acid (UA) is a bioactive compound which has demonstrated therapeutic efficacy in a variety of cancer cell lines. UA activates various signalling pathways in Glioblastoma multiforme (GBM), however, the relationship between cell death and migration has yet to be elucidated. UA induces a dose dependent cytotoxic response demonstrated by flow cytometry and biochemical cytotoxicity assays. Inhibitor and fluorescent probe studies demonstrated that UA induces a caspase independent, JNK dependent, mechanism of cell death. Migration studies established that UA inhibits GBM cell migration in a time dependent manner that is independent of the JNK signalling pathway. The cytotoxic insult induced by UA resulted in the formation of acidic vesicle organelles (AVOs), speculating activation of autophagy. However, inhibitor and spectrophotometric analysis demonstrated that autophagy was not responsible for the formation of the AVOs and confocal microscopy identified the AVOs as lysosomes. Further investigation using isosurface visualisation of confocal imaging determined co-localisation of lysosomes with the previously identified acidic vesicles, thus providing evidence that lysosomes are likely to be playing a role in UA induced cell death. Collectively, our data identifies that UA rapidly induces a lysosomal associated mechanism of cell death in addition to UA acting as an inhibitor of GBM cell migration. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=128 SRC="FIGDIR/small/987578v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1b00447org.highwire.dtl.DTLVardef@e8e39eorg.highwire.dtl.DTLVardef@1b7d816org.highwire.dtl.DTLVardef@cb8d3b_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2020

Functional delineation of tissue-resident CD8 T cell heterogeneity during infection and cancer

Unremitting defense against diverse pathogens and malignancies requires a dynamic and durable immune response. Tissue-resident memory CD8+ T cells (TO_SCPLOWRMC_SCPLOW) afford robust protection against infection and cancer progression through continuous surveillance of non-lymphoid tissues. Here, we provide insight into how TO_SCPLOWRMC_SCPLOW confer potent and persistent immunity through partitioning of distinct cellular subsets differing in longevity, effector function, and multipotency. Antigen-specific CD8+ T cells localized to the epithelium of the small intestine are primarily comprised of a shorter-lived effector population most prominent early following both acute viral and bacterial infections, and a longer-lived Id3hi TO_SCPLOWRMC_SCPLOW population that subsequently accumulates at later memory timepoints. We define regulatory gene-programs driving these distinct TO_SCPLOWRMC_SCPLOW states, and further clarify roles for Blimp1, T-bet, Id2, and Id3 in supporting and maintaining intestinal TO_SCPLOWRMC_SCPLOW heterogeneity during infection. Further, through single-cell RNAseq analysis we demonstrate that tumor-infiltrating lymphocytes broadly differentiate into discrete populations of short-lived and long-lived TO_SCPLOWRMC_SCPLOW-like subsets, which share qualities with terminally-exhausted and progenitor-exhausted cells, respectively. As the clinical relevance of TO_SCPLOWRMC_SCPLOW continues to widen from acute infections to settings of chronic inflammation and malignancy, clarification of the spectrum of phenotypic and functional states exhibited by CD8+ T cells that reside in non-lymphoid tissues will provide a framework for understanding their regulation and identity in diverse pathophysiological contexts.

immunology↗

bioRxiv2020

Molecular determinants and heterogeneity of tissue-resident memory CD8+ T lymphocytes revealed by single-cell RNA sequencing

During an immune response to microbial infection, CD8+ T cells give rise to distinct classes of cellular progeny that coordinately mediate clearance of the pathogen and provide long-lasting protection against reinfection, including a subset of non-circulating tissue-resident memory (TRM) cells that mediate potent protection within non-lymphoid tissues. Here, we utilized single-cell RNA-sequencing to examine the gene expression patterns of individual CD8+ T cells in the spleen and small intestine intraepithelial lymphocyte (siIEL) compartment throughout the course of their differentiation in response to viral infection. These analyses revealed previously unknown transcriptional heterogeneity within the siIEL CD8+ T cell population at several states of differentiation, representing functionally distinct TRM cell subsets as well as a subset of TRM cell precursors within the tissue early in infection. Taken together, these findings may inform strategies to optimize CD8+ T cell responses to protect against microbial infection and cancer. One sentence summaryHere, we applied single-cell RNA-sequencing to elucidate the gene expression patterns of individual CD8+ T cells differentiating throughout the course of infection in the spleen and small intestinal epithelium, which revealed previously unidentified molecular determinants of tissue-resident T cell differentiation as well as functional heterogeneity within the tissue-resident CD8+ T cell population.

immunology↗

bioRxiv2020

Cold Atmospheric Plasma induces silver nanoparticle uptake, oxidative dissolution and enhanced cytotoxicity in Glioblastoma multiforme cells

Silver nanoparticles (AgNP) emerged as a promising reagent for cancer therapy with oxidative stress implicated in the toxicity. Meanwhile, studies reported cold atmospheric plasma (CAP) generation of reactive oxygen and nitrogen species has selectivity towards cancer cells. Gold nanoparticles display synergistic cytotoxicity when combined with CAP against cancer cells but there is a paucity of information using AgNP, prompting to investigate the combined effects of CAP using dielectric barrier discharge system (voltage of 75 kV, current is 62.5mA, duty cycle of 7.5kVA and input frequency of 50-60Hz) and 10nm PVA-coated AgNP using U373MG Glioblastoma Multiforme cells. Cytotoxicity in U373MG cells was >100-fold greater when treated with both CAP and PVA-AgNP compared with either therapy alone (IC50 of 4.30 g/mL with PVA-AgNP alone compared with 0.07 g/mL after 25s CAP and 0.01 g/mL 40s CAP). Combined cytotoxicity was ROS-dependent and was prevented using N-Acetyl Cysteine. A novel darkfield spectral imaging method investigated and quantified AgNP uptake in cells determining significantly enhanced uptake, aggregation and subcellular accumulation following CAP treatment, which was confirmed and quantified using atomic absorption spectroscopy. The results indicate that CAP decreases nanoparticle size, decreases surface charge distribution of AgNP and induces uptake, aggregation and enhanced cytotoxicity in vitro. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=65 SRC="FIGDIR/small/969758v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@6cacdcorg.highwire.dtl.DTLVardef@c8c9caorg.highwire.dtl.DTLVardef@381c5dorg.highwire.dtl.DTLVardef@1ce1ece_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2020

Cluster similarity spectrum integration of single-cell genomics data

Technologies to sequence the transcriptome, genome or epigenome from thousands of single cells in an experiment provide extraordinary resolution into the molecular states present within a complex biological system at any given moment. However, it is a major challenge to integrate single-cell sequencing data across experiments, conditions, batches, timepoints and other technical considerations. New computational methods are required that can integrate samples while simultaneously preserving biological information. Here, we propose an unsupervised reference-free data representation, Cluster Similarity Spectrum (CSS), where each cell is represented by its similarities to clusters independently identified across samples. We show that CSS can be used to assess cellular heterogeneity and enable reconstruction of differentiation trajectories from cerebral organoid single-cell transcriptomic data, and to integrate data across experimental conditions and human individuals. We compare CSS to other integration algorithms and show that it can outperform other methods in certain integration scenarios. We also show that CSS allows projection of single-cell genomic data of different modalities to the CSS-represented reference atlas for visualization and cell type identity prediction. In summary, CSS provides a straightforward and powerful approach to understand and integrate challenging single-cell multi-omic data.

bioinformatics↗

bioRxiv2020

Lower Soil Carbon Loss Due to Persistent Microbial Adaptation to Climate Warming

Soil microbial respiration is an important source of uncertainty in projecting future climate and carbon (C) cycle feedbacks. Despite intensive studies for two decades, the magnitude, direction, and duration of such feedbacks are uncertain, and their underlying microbial mechanisms are still poorly understood. Here we examined the responses of soil respiration and microbial community structure to long-term experimental warming in a temperate grassland ecosystem. Our results indicated that the temperature sensitivity of soil microbial respiration (i.e., Q10) persistently decreased by 12.0{+/-}3.7% across 7 years of warming. Integrated metagenomic and functional analyses showed that microbial community adaptation played critical roles in regulating respiratory acclimation. Incorporating microbial functional gene abundance data into a microbially-enabled ecosystem model significantly improved the modeling performance of soil microbial respiration by 5-19%, compared to the traditional non-microbial model. Model parametric uncertainty was also reduced by 55-71% when gene abundances were used. In addition, our modeling analyses suggested that decreased temperature sensitivity could lead to considerably less heterotrophic respiration (11.6{+/-}7.5%), and hence less soil C loss. If such microbially mediated dampening effects occur generally across different spatial and temporal scales, the potential positive feedback of soil microbial respiration in response to climate warming may be less than previously predicted.

ecology↗

bioRxiv2020

High contiguity long read assembly of Brassica nigra allows localization of active centromeres and provides insights into the ancestral Brassica genome.

High-quality nanopore genome assemblies were generated for two Brassica nigra genotypes (Ni100 and CN115125); a member of the agronomically important Brassica species. The N50 contig length for the two assemblies were 17.1 Mb (58 contigs) and 0.29 Mb (963 contigs), respectively, reflecting recent improvements in the technology. Comparison with a de novo short read assembly for Ni100 corroborated genome integrity and quantified sequence related error rates (0.002%). The contiguity and coverage allowed unprecedented access to low complexity regions of the genome. Pericentromeric regions and coincidence of hypo-methylation enabled localization of active centromeres and identified a novel centromere-associated ALE class I element which appears to have proliferated through relatively recent nested transposition events (<1 million years ago). Computational abstraction was used to define a post-triplication Brassica specific ancestral genome and to calculate the extensive rearrangements that define the genomic distance separating B. nigra from its diploid relatives.

genomics↗