Biology subjects

Zuo, W.

Publications and source records attributed to Zuo, W..

36 records · Page 2Linked to original sources

bioRxiv2022

DANCE: A Deep Learning Library and Benchmark for Single-Cell Analysis

In the realm of single-cell analysis, computational approaches have brought an increasing number of fantastic prospects for innovation and invention. Meanwhile, it also presents enormous hurdles to reproducing the results of these models due to their diversity and complexity. In addition, the lack of gold-standard benchmark datasets, metrics, and implementations prevents systematic evaluations and fair comparisons of available methods. Thus, we introduce the DANCE platform, the first standard, generic, and extensible benchmark platform for accessing and evaluating computational methods across the spectrum of benchmark datasets for numerous single-cell analysis tasks. Currently, DANCE supports 3 modules and 8 popular tasks with 32 state-of-art methods on 21 benchmark datasets. People can easily reproduce the results of supported algorithms across major benchmark datasets via minimal efforts (e.g., only one command line). In addition, DANCE provides an ecosystem of deep learning architectures and tools for researchers to develop their own models conveniently. The goal of DANCE is to accelerate the development of deep learning models with complete validation and facilitate the overall advancement of single-cell analysis research. DANCE is an open-source python package that welcomes all kinds of contributions. All resources are integrated and available at https://omicsml.ai/.

bioinformatics↗

bioRxiv2022

Cell wall damage increases macromolecular crowding effects in the Escherichia coli cytoplasm

The intracellular milieu is crowded with biomacromolecules. Macromolecular crowding changes the interactions, diffusion, and conformations of the biomacromolecules. Changes in intracellular crowding effects have been mostly ascribed to differences in biomacromolecule concentration. However, the spatial organization of these molecules should play a significant role in crowding effects. Here, we find that cell wall damage causes increased macromolecular crowding effects in the Escherichia coli cytoplasm. Using a genetically-encoded macromolecular crowding sensor, we see that crowding effects in E. coli spheroplasts and Penicillin G-treated cells well surpass crowding effects obtained using hyperosmotic stress. The crowding increase is not due to osmotic pressure, cell shape, crowder synthesis, or volume changes, and therefore not crowder concentration. Instead, a genetically-encoded nucleic acid stain and a small molecule DNA stain show nucleoid expansion and cytoplasmic mixing, which could cause these increased crowding effects. Our data demonstrate that cell stress from antibiotics or cell wall damage alters the biochemical organization in the cytoplasm and induces significant conformational changes in a probe protein.

biophysics↗

bioRxiv2021

Reference genomes of 545 silkworms enable high-throughput exploring genotype-phenotype relationships

The silkworm Bombyx mori is a domestic insect for silk production and a lepidopteran model. The currently available genomes limit a full understanding of its genetic and phenotypic diversity. Here we assembled long-read genomes of 545 domestic and wild silkworms and constructed a high-resolution pan-genome dataset. We found that the silkworm population harbors extremely variable genomes containing 7,308 new gene families, 4,260 (22%) core gene families, and 3,432,266 non-redundant SVs. We deciphered a series of causal genes and variants associated with domestication, breeding, and ecological adaptation traits, and experimentally validated two of those genes using CRISPR-Cas9 or RNA interference. This unprecedented large-scale genomic resource allows for high-throughput screening of interesting traits for functional genomic research and breeding improvement of silkworms and may serve as a guideline for traits decoding in other species.

genomics↗

bioRxiv2021

EXPLICIT-Kinase: a gene expression predictor for dissecting the functions of the Arabidopsis kinome

Protein kinases regulate virtually all cellular processes, but it remains challenging to determine the functions of all protein kinases, collectively called the kinome, in any species. We developed an approach called EXPLICIT-Kinase to predict the functions of the Arabidopsis kinome. Because the activities of many kinases can be regulated transcriptionally, their gene expression patterns provide clues to their functions. A universal gene expression predictor for Arabidopsis was constructed to predict the expression of 30,172 non-kinase genes based on the expression of 994 protein kinase genes. The model reconstituted highly accurate transcriptomes for diverse Arabidopsis samples. It identified the significant kinases as predictor kinases for predicting the expression of Arabidopsis genes and pathways. Strikingly, these predictor kinases were often known regulators of the related pathways, as exemplified by those involved in cytokinesis, tissue development, and stress responses. Comparative analyses have revealed that portions of these predictor kinases, including the novel ones, are shared and conserved between Arabidopsis and maize. The conservation between species provide additional evidence to support the novel predictor kinases as bona fide regulators of the pathways involved. Thus our approach enables the systematic dissection of the functions of the Arabidopsis kinome.

systems biology↗

bioRxiv2021

Spatial profiling of microbial communities by sequential FISH with error-robust encoding

Spatial analysis of microbiomes at single cell resolution with high multiplexity and accuracy has remained challenging. Here we present spatial profiling of a microbiome using sequential error-robust fluorescence in situ hybridization (SEER-FISH), a highly multiplexed and accurate imaging method that allows mapping of microbial communities at micron-scale. We show that multiplexity of RNA profiling in microbiomes can be increased significantly by sequential rounds of probe hybridization and dissociation. Combined with error-correction strategies, we demonstrate that SEER-FISH enables accurate taxonomic identification in complex microbial communities. Using microbial communities composed of diverse bacterial taxa isolated from plant rhizospheres, we show that SEER-FISH can quantify the abundance of each taxon and map microbial biogeography on roots. SEER-FISH should enable accurate spatial profiling of the ecology and function of complex microbial communities.

microbiology↗

bioRxiv2020

Effectors with different gears: divergence of Ustilago maydis effector genes is associated with their temporal expression pattern during plant infection

Plant pathogens secrete a variety of effector proteins that enable host colonization but are also typical pathogen detection targets for the host immune system. Consequently, effector genes encounter high selection pressures, which typically makes them fast evolving. The corn smut pathogen Ustilago maydis has an effector gene repertoire with a dynamic expression across the different disease stages. We determined the amino acid divergence of U. maydis effector candidates with Sporisorium reilianum orthologs, a close relative of U. maydis. Intriguingly, there are two distinct groups of effector candidates, ones with a respective conserved and diverged protein evolution. Conservatively evolving effector genes especially have their peak expression during the (pre-)penetration stages of the disease cycle. In contrast, expression of divergently evolving effector genes generally peaks during fungal proliferation within the host. To test if this interspecific effector diversity corresponds to intraspecific diversity, we sampled and sequenced a diverse collection of U. maydis strains from the most important maize breeding and production regions in China. Effector candidates with a diverged interspecific evolution had more intraspecific amino acid variation than candidates with a conserved evolution. In conclusion, we highlight diversity in evolution within the U. maydis effector repertoire with dynamically and conservatively evolving members.

genomics↗

bioRxiv2020

Life-history dynamics: damping time, demographic dispersion and generation time

Transient dynamics are crucial for understanding ecological and life-history dynamics. In this study, we analyze damping time, the time taken by a population to converge to a stable (st)age structure following a perturbation, for over 600 species of animals and plants. We expected damping time to be associated with both generation time Tc and demographic dispersion{sigma} based on previous theoretical work. Surprisingly, we find that damping time (calculated from the population projection matrix) is approximately proportional to Tc across taxa on the log-log scale, regardless of{sigma} . The result suggests that species at the slow end of fast-slow continuum (characterized with long generation time, late maturity, low fecundity) are more vulnerable to external disturbances as they take more time to recover compared to species with fast life-histories. The finding on damping time led us to next examine the relationship between generation time and demographic dispersion. Our result reveals that the two life-history variables are positively correlated on a log-log scale across taxa, implying long generation time promotes demographic dispersion in reproductive events. Finally, we discuss our results in the context of metabolic theory and contribute to existing allometric scaling relationships.

ecology↗

bioRxiv2020

Cross-species analysis between the maize smut fungi Ustilago maydis and Sporisorium reilianum highlights the role of transcriptional plasticity of effector orthologs for virulence and disease

O_LIThe constitution and regulation of effector repertoires determines and shapes the outcome of the interaction with the host. Ustilago maydis and Sporisorium reilianum are two closely related smut fungi, which both infect maize, but cause distinct disease symptoms. Understanding how effector orthologs are regulated in these two pathogens can therefore provide insights to pathogen evolution and host adaption. C_LIO_LIWe tracked the infection progress of U. maydis and S. reilianum in maize leaves, characterized two distinct infection stages for cross species RNA-sequencing analysis and identified 207 out of 335 one-to-one effector orthologs being differentially regulated during host colonization, while transcriptional plasticity of the effector orthologs correlated with the distinct disease development strategies. C_LIO_LIBy using CRISPR-Cas9 mediated gene conversion, we identified two differentially expressed effector orthologs with conserved function between two pathogens. Thus, differential expression of functionally conserved genes contributes to species specific adaptation and symptom development. Interestingly, another differentially expressed orthogroup (UMAG_05318/Sr1007) showed diverged protein function during speciation, providing a possible case for neofunctionalization. C_LIO_LICollectively, we showed the diversification of effector genes in related pathogens can be caused both by plasticity on the transcriptional level, as well as through functional diversification of the encoded effector proteins. C_LI

plant biology↗

bioRxiv2020

Single-cell analysis reveals the function of lung progenitor cells in COVID-19 patients

The high mortality of severe 2019 novel coronavirus disease (COVID-19) cases is mainly caused by acute respiratory distress syndrome (ARDS), which is characterized by increased permeability of the alveolar epithelial barriers, pulmonary edema and consequently inflammatory tissue damage. Some but not all patients showed full functional recovery after the devastating lung damage, and so far there is little knowledge about the lung repair process1. Here by analyzing the bronchoalveolar lavage fluid (BALF) of COVID-19 patients through single cell RNA-sequencing (scRNA-Seq), we found that in severe (or critical) cases, there is remarkable expansion of TM4SF1+ and KRT5+ lung progenitor cells. The two distinct populations of progenitor cells could play crucial roles in alveolar cell regeneration and epithelial barrier re-establishment, respectively. In order to understand the function of KRT5+ progenitors in vivo, we transplanted a single KRT5+ cell-derived cell population into damaged mouse lung. Time-course single-cell transcriptomic analysis showed that the transplanted KRT5+ progenitors could long-term engrafted into host lung and differentiate into HOPX+ OCLN+ alveolar barrier cell which restored the epithelial barrier and efficiently prevented inflammatory cell infiltration. Similar barrier cells were also identified in some COVID-19 patients with massive leukocyte infiltration. Altogether this work uncovered the mechanism that how various lung progenitor cells work in concert to prevent and replenish alveoli loss post severe SARS-CoV-2 infection.

bioinformatics↗

bioRxiv2020

Distributions of LRS in varying environments

Studies of lifetime reproductive success (LRS) have shown that important random events can be in ecology and evolution. Randomness should be amplified in stochastic environments, and here we show here we show this to be the case by computing the complete distribution of LRS when vital rates are Markovian can be readily computed by building on our recent paper (Tuljapurkar et al. 2020). These results complement the work of van Daalen and Caswell (2020) on moments of LRS. We use empirical studies of Roe deer, Capreolus capreolus, to show that environments at birth have strong effects on future performance, and that analyses of the LRS in stochastic environments are a valuable element of studies of the consequences of climate change.

ecology↗

bioRxiv2020

Single-cell RNA expression profiling of ACE2, the putative receptor of Wuhan 2019-nCov

A novel coronavirus SARS-CoV-2 was identified in Wuhan, Hubei Province, China in December of 2019. According to WHO report, this new coronavirus has resulted in 76,392 confirmed infections and 2,348 deaths in China by 22 February, 2020, with additional patients being identified in a rapidly growing number internationally. SARS-CoV-2 was reported to share the same receptor, Angiotensin-converting enzyme 2 (ACE2), with SARS-CoV. Here based on the public database and the state-of-the-art single-cell RNA-Seq technique, we analyzed the ACE2 RNA expression profile in the normal human lungs. The result indicates that the ACE2 virus receptor expression is concentrated in a small population of type II alveolar cells (AT2). Surprisingly, we found that this population of ACE2-expressing AT2 also highly expressed many other genes that positively regulating viral entry, reproduction and transmission. This study provides a biological background for the epidemic investigation of the COVID-19, and could be informative for future anti-ACE2 therapeutic strategy development.

bioinformatics↗

bioRxiv2020

Isolation and long-term expansion of a single adult human renal epithelial cell with efficient kidney regeneration capacity

A wide spectrum of lethal kidney diseases involves the irreversible destruction of the tubular structures which leads to loss of renal function. A reliable technological platform to culture and transplant adult human-derived cells with nephrogenic potential offers great hope to facilitate human kidney regeneration. Here, we show that in an appropriate feeder cell-based culture system, it is feasible to isolate and long-term expand the progenitor-like SOX9+ renal epithelial cells (SOX9+ RECs) from adult mammalians. Single cell-derived SOX9+ REC lines can be established from human needle biopsy or urine samples with molecular homogeneity and genomic stability maintained during culture. Such cells grown in 3D culture system could self-organize into renal organoids composed of proximal tubular, Loop of Henle (LOH) and distal tubular cells as illustrated by single cell transcriptomic analysis. Once being transplanted into the physically injured mouse kidney, the expanded single human SOX9+ RECs incorporated into the damaged area and demonstrated capacity of regenerating functional tubules in vivo. Altogether, the ability to extensively propagate human SOX9+ REC in culture whilst concomitantly maintaining their intrinsic lineage differentiation commitment suggests their future application in regenerative medicine.

cell biology↗

bioRxiv2019

Skewed distributions of LRS: beyond mean and variance

Many field studies find that lifetime reproductive success (LRS) is highly skewed and often multimodal among individuals. Field biologists generate invaluable data on survival and reproductive rates, as a function of age and stage, that are used to parameterise structured models. These models often perform well at predicting population growth and mean LRS, but we do not know whether they accurately predict observed distributions of individual LRS. If the models fail to recreate these distributions, their use may be limited because the LRS is central to understanding life history evolution. We present powerful tools to generate distributions of LRS from age and/or stage structured models. Our methods reveal that structured models do perform well at generating distributions that agree with observations. Our approach also reveals why such skewed distributions arise, and helps resolve a debate about detecting signatures of selection in skewed distributions of LRS.

ecology↗

bioRxiv2019

Cas9HF1 enhanced specificity in Ustilago maydis

The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 system is widely used as a tool to precisely manipulate genomic sequence targeted by sgRNA (single guide RNA) and is adapted in different species for genome editing. One of the major concerns of CRISPR-Cas9 is the possibility of off-target effects, which can be remedied by the deployment of high fidelity Cas9 variants. Ustilago maydis is a maize fungal pathogen, which has served as a model organism for biotrophic pathogens for decades. The successful adaption of CRISPR-Cas9 in U. maydis greatly facilitated effector biology studies. Here, we constructed an U. maydis reporter strain that allows in vivo quantification of efficiency and target specificity of three high fidelity Cas9 variants, Cas9HF1, Cas9esp1.1 and Cas9hypa. This approach identified Cas9HF1 as most specific Cas9 variant in U. maydis. Furthermore, whole genome sequencing showed absence of off-target effects in U. maydis by CRISPR-Cas9 editing.

genetics↗

bioRxiv2019

Gene modules associated with human diseases revealed by network analysis

Despite many genes associated with human diseases have been identified, disease mechanisms often remain elusive due to the lack of understanding how disease genes are connected functionally at pathways level. Within biological networks, disease genes likely map to modules whose identification facilitates etiology studies but remains challenging. We describe a systematic approach to identify disease-associated gene modules. A gene co-expression network based on the graphical Gaussian model (GGM) was constructed using the GTEx dataset and assembled into 652 gene modules. Screening these modules identified those with disease genes enrichment for obesity, cardiomyopathy, hypertension, and autism, which illuminated the molecular pathways underlying their pathogenesis. Using mammalian phenotypes derived from mouse models, potential disease candidate genes were identified from these modules. Also analyzed were epilepsy, schizophrenia, bipolar disorder, and depressive disorder, revealing shared and distinct disease modules among brain disorders. Thus, disease genes converge on modules within our GGM gene co-expression network, which provides a general framework to dissect genetic architecture of human diseases.

systems biology↗

bioRxiv2018

Age Distribution, Trends, and Forecasts of Under-5 Mortality in Sub-Saharan Africa

BackgroundDespite the sharp decline in global under-5 deaths since 1990, uneven progress has been achieved across and within countries. In Sub-Saharan Africa, the Millennium Development Goals targets for child mortality were met only by a few countries, and recently new targets were set in goals for Sustainable Development that include the eradication of preventable deaths by reducing neonatal and under-5 mortality rates to at least as low 12 and 25 per 1000 live births by 2030, respectively. As the reduction of preventable deaths has a direct impact on their age distribution, the foci of this study are assessing age patterns, trends over time, and forecasts of mortality rates in Sub-Saharan Africa.\n\nMethods and findingsData came from 104 nationally-representative Demographic and Health Surveys with full birth histories from 31 Sub-Saharan African countries from 1990 to 2016 (a total of 448 country-years of data). We assessed the distribution of age at death through the following demographic model. First, we used a direct method for the estimation of death rates with full-birth histories from survey data to construct age profiles of under-5 mortality on a monthly basis. Second, a two-dimensional P-spline approach was used to smooth out raw estimates of death rates by age and time. Third, a variant of the Lee-Carter model, designed for populations with limited data, was used to fit and forecast age profiles of mortality. We used mortality estimates from the United Nations Inter-agency group for Child Mortality Estimation to adjust, validate and minimize the risk of bias in survival, truncation, and recall in mortality estimation.\n\nOur study has three salient findings. First, we observe a monotonous decline of death rates at every age in most countries, but with notable differences in the age-patterns over time. Second, our projections of continued decline of child mortality differ from existing estimates from the United Nations Inter-agency group for Child Mortality Estimation in 5 countries for both neonatal and under-5 mortality. Finally, we predict that only 5 countries (Guinea, Liberia, Rwanda, Tanzania, and Uganda) are on track to achieve the sustainable development goal targets on child mortality by 2030. Poor data quality issues that include bias in the report of births and deaths, or age heaping, remain a limitation of this study.\n\nConclusionsThis study is the first to combine full birth history data and mortality estimates from external reliable sources to model age patterns of under-5 mortality across time in Sub-Saharan Africa. We demonstrate that countries with a rapid pace of mortality reduction across ages would be more likely to achieve the sustainable development goal targets of child mortality reduction. Our mortality model predicts that if neonatal and under-5 deaths decline at the rates observed during the last 25 years, only 5 countries would reach those targets by 2030, 15 would achieve them between 2030 and 2050, and 11 afterwards.

epidemiology↗

bioRxiv2018

An Advancing Front of Old Age Human Survival

Old age mortality decline has driven recent increases in lifespans, but there is no agreement about trends in the age-pattern of old deaths. Some hypotheses argue that old-age deaths should have become compressed at high ages, others that old-age deaths should have become more dispersed with age, and yet others are consistent with little change in dispersion. However, direct analyses of old-age deaths presents unusual challenges: death rates at the oldest ages are always noisy; published life tables must assume an asymptotic age pattern of deaths; and the definition of \"old age\" changes as lives lengthen. Here we use robust percentile-based methods to overcome these challenges and show, for 5 decades in 20 developed countries, that old-age survival follows an advancing front, like a traveling wave. The front lies between the 25th and 90th percentiles of old-age deaths, advancing with nearly constant long-term shape but annual fluctuations in speed. The existence of this front leads to several predictions that we verify, e.g., that advances in life expectancy at age 65 are highly correlated with the advance of the 25th percentile, but not with distances between higher percentiles. Our unexpected result has implications for biological hypotheses about human aging, and for future mortality change.

epidemiology↗

bioRxiv2017

Deficiency of Voltage-gated Proton Channel Hv1 Leads to hypoinsulinaemia, hyperglycemia and glucose intolerance in mice

Here, we demonstrate that the voltage-gated proton channel Hv1 represents a regulatory mechanism for insulin secretion of pancreatic islet {beta} cell. In vivo, Hv1-de[fi]cient mice display hyperglycemia and glucose intolerance due to reduced insulin secretion, but normal peripheral insulin sensitivity. In vitro, islets of Hv1-de[fi]cient and heterozygous mice, INS-1 (832/13) cells with siRNA-mediated knockdown of Hv1 exhibit a marked defect in glucose- and K+-induced insulin secretion. Hv1 de[fi]ciency decreases both insulin and proinsulin contents, and limits glucose-induced Ca2+ entry and membrane depolarization. Furthermore, loss of Hv1 increases insulin-containing granular pH and decreases cytosolic pH. In addition, histologic studies show a decrease in {beta} cell mass in islets of Hv1-deficient mice. Collectively, our results indicate that Hv1 supports insulin secretion in the {beta} cell by calcium entry, membrane depolarization and intracellular pH regulation.

cell biology↗