Biology subjects

Lin, M.

Publications and source records attributed to Lin, M..

At least 109 records · Page 6Linked to original sources

bioRxiv2021

TNFAIP8 is a novel phosphoinositide-binding inhibitory regulator of Rho GTPases that promotes cancer cell migration

More than half of human tumors exhibit aberrantly dysregulated phosphoinositide signaling, yet how this is controlled remains not fully understood. While somatic mutations of PI3K, PTEN and Ras account for many cases of the hyperactivated lipid signals, other mechanisms for these dysfunctions in cancer are also being discovered. We report here that TNFAIP8 interacts with PtdIns(4,5)P2 and PtdIns(3,4,5)P3 and is likely to be hijacked by cancer cells to facilitate directional migration during malignant transformation. TNFAIP8 maintains the quiescent cellular state by sequestering inactive Rho GTPases in the cytosolic pool, which can be set free upon chemoattractant activation at the leading edge. Consequently, loss of TNFAIP8 results in severe defects of chemotaxis and adhesion. Thus, TNFAIP8, whose expression can be induced by inflammatory cytokines such as TNF from tumor microenvironment, represents a molecular bridge from inflammation to cancer by linking NF-{kappa}B pathway to phosphoinositide signaling. Our study on the conserved hydrophobic cavity structure will also advise in silico drug screening and development of new TNFAIP8-based strategies to combat malignant human diseases.

cell biology↗

bioRxiv2021

Admixed Populations Improve Power for Variant Discovery and Portability in Genome-wide Association Studies

Genome-wide association studies (GWAS) are primarily conducted in single-ancestry settings. The low transferability of results has limited our understanding of human genetic architecture across a range of complex traits. In contrast to homogeneous populations, admixed populations provide an opportunity to capture genetic architecture contributed from multiple source populations and thus improve statistical power. Here, we provide a mechanistic simulation framework to investigate the statistical power and transferability of GWAS under directional polygenic selection or varying divergence. We focus on a two-way admixed population and show that GWAS in admixed populations can be enriched for power in discovery by up to 2-fold compared to the ancestral populations under similar sample size. Moreover, higher accuracy of cross-population polygenic score estimates is also observed if variants and weights are trained in the admixed group rather than in the ancestral groups. Common variant associations are also more likely to replicate if first discovered in the admixed group and then transferred to an ancestral population, than the other way around (across 50 iterations with 1,000 causal SNPs, training on 10,000 individuals, testing on 1,000 in each population, p=3.78e-6, 6.19e-101, ~0 for FST = 0.2, 0.5, 0.8, respectively). While some of these FST values may appear extreme, we demonstrate that they are found across the entire phenome in the GWAS catalog. This framework demonstrates that investigation of admixed populations harbors significant advantages over GWAS in single-ancestry cohorts for uncovering the genetic architecture of traits and will improve downstream applications such as personalized medicine across diverse populations.

genetics↗

bioRxiv2021

Post-transcriptional dysregulation in autism, schizophrenia and bipolar disorder

Post-transcriptional gene regulation (PTGR) contributes to numerous aspects of RNA metabolism. While multiple regulators of PTGR have been associated with the occurrence and development of psychiatric disorders, a systematic investigation of the role of PTGR in the context of neuropsychiatric disorders is still lacking. In this work, we developed a new transcriptome -based algorithm to estimate PTGR and applied it to an RNA-Seq dataset of 2160 brain samples from individuals with autism spectrum disorder (ASD), schizophrenia (SCZ), bipolar disorder (BD) and controls. The results showed that the contribution of PTGR abnormality to gene differential expression between three common psychiatric disorders and controls was about 30% of that of transcriptional gene regulation (TGR) abnormality. Besides, aberrant PTGR tended to decrease RNA stability in SCZ/BD, while increase RNA stability in ASD, implicating contrasting pathologies among diseases. The abnormal alteration of PTGR in SCZ/BD converged on the inhibition of neurogenesis and neural differentiation, whereas dysregulation of PTGR in ASD induced enhanced activity of apoptosis. This suggested that heterogeneity in disease mechanism and clinical manifestation across different psychiatric disorders may be partially attributed to the diverse role of PTGR. Intriguingly, we identified a promising RBP (RNA bind protein) ELAVL3 (ELAV-Like Protein 3) that have a profound role in all three psychiatric disorders. Our systematic study expands the understanding of the link between PTGR and psychiatric disorders and also open a new avenue for deciphering the pathogenesis of psychiatric disorders.

genomics↗

bioRxiv2021

Single-cell transcriptomics reveal cell type-specific molecular changes and altered intercellular communications in chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is a common and heterogeneous respiratory disease, the molecular complexity of which remains poorly understood, as well as the mechanisms by which aging and smoking facilitate COPD development. Here, using single-cell RNA sequencing of more than 65,000 cells from COPD and age-stratified control lung tissues of donors with different smoking histories, we identified monocytes, club cells, and macrophages as the most disease-, aging-, and smoking-relevant cell types, respectively. Notably, we found these highly cell-type specific changes under different conditions converged on cellular dysfunction of the alveolar epithelium. Deeper investigations revealed that the alveolar epithelium damage could be attributed to the abnormally activated monocytes in COPD lungs, which could be amplified via exhaustion of club cell stemness as ages. Moreover, the enhanced intercellular communications in COPD lungs as well as the pro-inflammatory interaction between macrophages and endothelial cells indued by smoking could facilitate signaling between monocyte and the alveolar epithelium. Our findings complement the existing model of COPD pathogenesis by emphasizing the contributions of the previously less appreciated cell types, highlighting their candidacy as potential therapeutic targets for COPD.

pathology↗

bioRxiv2021

SnapKin: a snapshot deep learning ensemble for kinase-substrate prediction from phosphoproteomics data

Mass spectrometry (MS)-based phosphoproteomics enables the quantification of proteome-wide phosphorylation in cells and tissues. A major challenge in MS-based phosphoproteomics lies in identifying the substrates of kinases, as currently only a small fraction of substrates identified can be confidently linked with a known kinase. By leveraging large-scale phosphoproteomics data, machine learning has become an increasingly popular approach for computationally predicting substrates of kinases. However, the small number of high-quality experimentally validated kinase substrates (true positive) and the high data noise in many phosphoproteomics datasets together impact the performance of existing approaches. Here, we aim to develop advanced kinase-substrate prediction methods to address these challenges. Using a collection of seven large phosphoproteomics datasets, including six published datasets and a new muscle differentiation dataset, and both traditional and deep learning models, we first demonstrate that a pseudo-positive learning strategy for alleviating small sample size is effective at improving model predictive performance. We next show that a data re-sampling based ensemble learning strategy is useful for improving model stability while further enhancing prediction. Lastly, we introduce an ensemble deep learning model ( SnapKin) incorporating the above two learning strategies into a snapshot ensemble learning algorithm. We demonstrate that the SnapKin model achieves overall the best performance in kinase-substrate prediction. Together, we propose SnapKin as a promising approach for predicting substrates of kinases from large-scale phosphoproteomics data. SnapKin is freely available at https://github.com/PYangLab/SnapKin.

bioinformatics↗

bioRxiv2021

In vivo generation of BK and JC polyomavirus defective viral genomes in human urine samples associated with higher viral loads

Defective viral genomes (DVGs) are parasitic viral sequences containing point mutations, deletions, or duplications that might interfere with replication. DVGs are often associated with viral passage at high multiplicities of infection in culture systems but have been increasingly reported in clinical specimens. To date however, only RNA viruses have been shown to contain DVGs in clinical specimens. Here, using direct deep sequencing with multiple library preparation strategies and confirmatory ddPCR of urine samples taken from immunosuppressed individuals, we show clinical BKPyV and JCPyV strains contain widespread genomic rearrangements across multiple loci that likely interfere with viral replication. BKPyV DVGs were universally derived from type I subtype BKPyV. The presence of DVGs was associated with specimens containing higher viral loads but never reached clonality, consistent with a model of parasitized replication. These DVGs persisted during clinical infection as evidenced in two separate pairs of samples containing BK virus collected from the same individual up to 302 days apart. In a separate individual, we observed the generation of DVGs after a 57.5-fold increase in viral load. In summary, by extending the presence of DVGs in clinical specimens to DNA viruses, we demonstrate the ubiquity of DVGs in clinical virology. IMPORTANCEDefective viral genomes (DVGs) can have a significant impact on the production of infectious virus particles. DVGs have only been identified in cultured viruses passaged at high multiplicities of infection and RNA viruses collected from clinical specimens -- no DNA virus in the wild has been shown to contain DVGs. Here, we identified BK and JC polyomavirus DVGs in clinical urine specimens and demonstrated that these DVGs are more frequently identified in samples with higher viral loads. The strains containing DVGs had rearrangements throughout their genomes with the majority affecting genes required for viral replication. Longitudinal analysis showed these DVGs can persist during an infection, but do not reach clonality within the chronically infected host. Our identification of polyomavirus DVGs suggests these parasitic sequences exist across the many classes of viruses capable of causing human disease.

microbiology↗

bioRxiv2021

Optical regulation of endogenous RhoA reveals switching of cellular responses by signal amplitude

How protein signaling networks respond to different input strengths is an important but poorly understood problem in cell biology. For example, the small GTPase RhoA regulates both focal adhesion (FA) growth or disassembly, but whether RhoA serves as a switch selecting between cellular outcomes, or if outcomes are simply modulated by additional factors in the cell, is not clear. Here, we develop a photoswitchable RhoA guanine exchange factor, psRhoGEF, to precisely control endogenous RhoA activity. We also develop a FRET-based biosensor to allow visualization of RhoA activity together with psRhoGEF control. Using these new optical tools, we discover that low levels of RhoA activation preferentially induce FA disassembly in a Src-dependent manner, while high levels induce both FA growth and disassembly in a ROCK-dependent manner. Thus, rheostatic control of RhoA activation with photoswitchable RhoGEF reveals that cells can use signal amplitude to produce multiple responses to a single biochemical signal.

bioengineering↗

bioRxiv2021

From zero to infinity: minimum to maximum diversity of the planet by spatio-parametric Rao's quadratic entropy

AimThe majority of work done to gather information on Earth diversity has been carried out by in-situ data, with known issues related to epistemology (e.g., species determination and taxonomy), spatial uncertainty, logistics (time and costs), among others. An alternative way to gather information about spatial ecosystem variability is the use of satellite remote sensing. It works as a powerful tool for attaining rapid and standardized information. Several metrics used to calculate remotely sensed diversity of ecosystems are based on Shannons Information Theory, namely on the differences in relative abundance of pixel reflectances in a certain area. Additional metrics like the Raos quadratic entropy allow the use of spectral distance beside abundance, but they are point descriptors of diversity, namely they can account only for a part of the whole diversity continuum. The aim of this paper is thus to generalize the Raos quadratic entropy by proposing its parameterization for the first time. InnovationThe parametric Raos quadratic entropy, coded in R, i) allows to represent the whole continuum of potential diversity indices in one formula, and ii) starting from the Raos quadratic entropy, allows to explicitly make use of distances among pixel reflectance values, together with relative abundances. Main conclusionsThe proposed unifying measure is an integration between abundance- and distance-based algorithms to map the continuum of diversity given a satellite image at any spatial scale.

ecology↗

bioRxiv2020

Negative durotaxis: cell movement toward softer environments

Durotaxis - the ability of cells to sense and migrate along stiffness gradients - is important for embryonic development and has been implicated in pathologies including fibrosis and cancer. Although cellular processes can sometimes turn toward softer environments, durotaxis at the level of cells has thus far been observed exclusively as migration from soft to stiff regions. The molecular basis of durotaxis, especially the factors that contribute to different durotactic behaviors in various cell types, are still inadequately understood. With the recent discovery of optimal stiffness, where cells generate maximal traction forces on substrates in an intermediate stiffness range, we hypothesized that some migratory cells may be capable of moving away from stiff environments and toward matrix on which they can generate more traction. Combining hydrogel-based stiffness gradients, live-cell imaging, genetic manipulations, and computational modeling, we found that cells move preferentially toward their stiffness optimum for maximal force transmission. Importantly, we directly observed biased migration toward softer environments, i.e. negative durotaxis, in human glioblastoma cells. This directional migration did not coincide with changes in FAK, ERK or YAP signaling, or with altered actomyosin contractility. Instead, integrin-mediated adhesion and motor-clutch dynamics alone are sufficient to generate asymmetric traction to drive both positive and negative durotaxis. We verified this mechanistically by applying a motor-clutch-based model to explain negative durotaxis in the glioblastoma cells and in neurites, and experimentally by switching breast cancer cells from positive to negative durotaxis via talin downregulation. Our results identify the likely molecular mechanisms of durotaxis, with a cells contractile and adhesive machinery dictating its capacity to exert traction on mechanically distinct substrates, directing cell migration.

biophysics↗

bioRxiv2020

The Biogeography of Fungal Communities Across Different Chinese Wine-producing Regions Associated with Environmental Factors and Spontaneous Fermentation Performance

Chinese Marselan grapes are believed to possess the potential to become a characteristic regional variety, whose quality is internationally recognized. The fermentation-related mycobiota from six climatically diverse Marselan-producing regions in China were analyzed via high-throughput sequencing (HTS), while the influence of environmental factors was evaluated as well. The results implied that the phyla Ascomycota and genus Aureobasidium dominated the fungal communities in 166 Marselan must and ferment samples. Significant differences were detected in the fungal microbiota from the regions, as well as the wineries, while these discrepancies decreased as the fermentation progressed. Moreover, the difference in fungal communities between the wineries exceeded the variation involving the regions, and higher diversity was identified in the types of species than in the compositions. Geoclimatic elements (Gc) and physicochemical indexes (Pi) exerted a significant effect on the fungal must consortium, explaining 58.17% of the taxonomic information. Therefore, a correlation was proposed between the spontaneous fermentation performance, as well as the polyphenol (PP) content, and their association with fungal taxonomic composition. In addition to enriching the knowledge regarding the wine microbiome and its influencing factors, this study may provide a new strategy for harnessing autochthonous "microbial terroir". ImportanceWine microbiome and their metabolism play a crucial role in wine quality. Chinese wine-producing regions are widely distributed with diverse geoclimatic conditions, this study reports a most comprehensive biogeography of fermentation-related fungal communities performed to date, taking the Chinese promising Marselan grape variety as the research object. It reveals significant differences in the fungal microbiota of Marselan must and ferment from different regions and wineries, and higher otherness between species type than that between species composition. The study also reports the main geoclimatic and physicochemical factors shaping fungal flora. Moreover, a correlation was proposed among the spontaneous fermentation performance with fungal taxonomic composition and polyphenol content. Taken together, the results shed light on the wine fungal communities and its influencing factors, which is crucial for vineyard and fermentation microorganism management, and may also provide a new strategy for harnessing autochthonous "microbial terroir" by utilizing spontaneous fermentation.

microbiology↗

bioRxiv2020

Motor variability prior to learning is a poor predictor of the ability to adopt new movement solutions

Many contexts in motor learning require a learner to change from an existing movement solution to a novel movement solution to perform the same task. Recent evidence has pointed to motor variability prior to learning as a potential marker for predicting individual differences in motor learning. However, it is not known if this variability is predictive of the ability to adopt a new movement solution for the same task. Here, we examined this question in the context of a redundant precision task requiring control of motor variability. Fifty young adults learned a precision task that involved throwing a virtual puck toward a target using both hands. Because the speed of the puck depended on the sum of speeds of both hands, this task could be achieved using multiple solutions. Participants initially performed a baseline task where there was no constraint on the movement solution, and then performed a novel task where they were constrained to adopt a specific movement solution requiring asymmetric left and right hand speeds. Results showed that participants were able to learn the new solution, and this change was associated with changes in both the amount and structure of variability. However, individual differences in baseline motor variability were only weakly correlated with initial and final task performance when using the new solution, with greater variability being associated with higher errors. We also found a strong specificity component - initial variability when using the new solution was highly correlated with final task performance with the new solution, but once again, higher variability was associated with greater errors. These results suggest that motor variability is not necessarily indicative of flexibility and highlight the need to consider the task context in determining the relation between motor variability and learning.

neuroscience↗

bioRxiv2020

A red fluorescent protein with improved monomericity enables ratiometric voltage imaging with ASAP3

A ratiometric genetically encoded voltage indicator (GEVI) would be desirable for tracking transmembrane voltage changes in cells that are undergoing motion. To create a high-performance ratiometric GEVI, we explored the possibility of adding a voltage-independent red fluorophore to ASAP3, a high-gain green fluorescent GEVI. We performed combinatorial multi-site mutagenesis on the cyan-excitable red fluorescent protein mCyRFP1 to enhance brightness and monomericity, creating mCyRFP3. Among red fluorescent proteins tested, mCyRFP3 proved to be the least perturbing when fused to ASAP3. We demonstrate that the red fluorescence of ASAP3-mCyRFP3 (ASAP3-R3) provides an effective reference channel to remove motion artifacts from voltage-induced changes in green fluorescence. Finally we use ASAP3-R3 to visualize membrane voltage changes throughout the cell cycle of motile cells.

cell biology↗

bioRxiv2020

Cellular Anatomy of the Mouse Primary Motor Cortex

An essential step toward understanding brain function is to establish a cellular-resolution structural framework upon which multi-scale and multi-modal information spanning molecules, cells, circuits and systems can be integrated and interpreted. Here, through a collaborative effort from the Brain Initiative Cell Census Network (BICCN), we derive a comprehensive cell type-based description of one brain structure - the primary motor cortex upper limb area (MOp-ul) of the mouse. Applying state-of-the-art labeling, imaging, computational, and neuroinformatics tools, we delineated the MOp-ul within the Mouse Brain 3D Common Coordinate Framework (CCF). We defined over two dozen MOp-ul projection neuron (PN) types by their anterograde targets; the spatial distribution of their somata defines 11 cortical sublayers, a significant refinement of the classic notion of cortical laminar organization. We further combine multiple complementary tracing methods (classic tract tracing, cell type-based anterograde, retrograde, and transsynaptic viral tracing, high-throughput BARseq, and complete single cell reconstruction) to systematically chart cell type-based MOp input-output streams. As PNs link distant brain regions at synapses as well as host cellular gene expression, our construction of a PN type resolution MOp-ul wiring diagram will facilitate an integrated analysis of motor control circuitry across the molecular, cellular, and systems levels. This work further provides a roadmap towards a cellular resolution description of mammalian brain architecture.

neuroscience↗

bioRxiv2020

Rational design of a new class of protease inhibitors for the potential treatment of coronavirus diseases

The coronavirus main protease, Mpro, is a key protein in the virus life cycle and a major drug target. Based on crystal structures of SARSCoV2 Mpro complexed with peptidomimetic inhibitors, we recognized a binding characteristic shared with proline-containing inhibitors of hepatitis C virus protease. Initial tests showed that this subclass of HCV protease inhibitors indeed exhibited activity against Mpro. Postulating a benefit for a preorganized backbone conformation, we designed new ketoamide-based Mpro inhibitors based on central proline rings. One of the designed compounds, ML1000, inhibits Mpro with low-nanomolar affinity and suppresses SARSCoV2 viral replication in human cells at sub-micromolar concentrations. Our findings identify ML1000 as a promising new pre-organized scaffold for the development of anti-coronavirus drugs.

biochemistry↗

bioRxiv2020

A Biodiversity Composition Map of California Derived from Environmental DNA Metabarcoding and Earth Observation

Unique ecosystems globally are under threat from ongoing anthropogenic environmental change. Effective conservation management requires more thorough biodiversity surveys that can reveal system-level patterns and that can be applied rapidly across space and time. We offer a way to use environmental DNA, community science and remote sensing together as methods to reduce the discrepancy between the magnitude of change and historical approaches to measure it. Taking advantages of modern ecological models, we integrate environmental DNA and Earth observations to evaluate regional biodiversity patterns for a snapshot of time, and provide critical community-level characterization. We collected 278 samples in Spring 2017 from coastal, shrub and lowland forest sites in California, a large-scale biodiversity hotspot. We applied gradient forest to model 915 family occurrences and community composition together with environmental variables and multi-scalar habitat classifications to produce a statewide biodiversity-based map. 16,118 taxonomic entries recovered were associated with environmental variables to test their predictive strength on alpha, beta, and zeta diversity. Local habitat classification was diagnostic of community composition, illuminating a characteristic of biodiversity hotspots. Using gradient forest models, environmental variables predicted 35% of the variance in eDNA patterns at the family level, with elevation, sand percentage, and greenness (NDVI32) as the top predictors. This predictive power was higher than we found in published literature at global scale. In addition to this indication of substantial environmental filtering, we also found a positive relationship between environmentally predicted families and their numbers of biotic interactions. In aggregate, these analyses showed that strong eDNA community-environment correlation is a general characteristic of temperate ecosystems, and may explain why communities easily destabilize under disturbances. Our study provides the first example of integrating citizen science based eDNA with biodiversity mapping across the tree of life, with promises to produce large scale, high resolution assessments that promote a more comprehensive and predictive understanding of the factors that influence biodiversity and enhance its maintenance.

ecology↗

bioRxiv2020

Different pattern of pre-existing SARS-COV-2 specific T cell immunity in SARS-recovered and uninfected individuals

Memory T cells induced by previous infections can influence the course of new viral infections. Little is known about the pattern of SARS-CoV-2 specific pre-existing memory T cells in human. Here, we first studied T cell responses to structural (nucleocapsid protein, NP) and non-structural (NSP-7 and NSP13 of ORF1) regions of SARS-CoV-2 in convalescent from COVID-19 (n=24). In all of them we demonstrated the presence of CD4 and CD8 T cells recognizing multiple regions of the NP protein. We then show that SARS-recovered patients (n=23), 17 years after the 2003 outbreak, still possess long-lasting memory T cells reactive to SARS-NP, which displayed robust cross-reactivity to SARS-CoV-2 NP. Surprisingly, we observed a differential pattern of SARS-CoV-2 specific T cell immunodominance in individuals with no history of SARS, COVID-19 or contact with SARS/COVID-19 patients (n=18). Half of them (9/18) possess T cells targeting the ORF-1 coded proteins NSP7 and 13, which were rarely detected in COVID-19- and SARS-recovered patients. Epitope characterization of NSP7-specific T cells showed recognition of protein fragments with low homology to "common cold" human coronaviruses but conserved among animal betacoranaviruses. Thus, infection with betacoronaviruses induces strong and long-lasting T cell immunity to the structural protein NP. Understanding how pre-existing ORF-1-specific T cells present in the general population impact susceptibility and pathogenesis of SARS-CoV-2 infection is of paramount importance for the management of the current COVID-19 pandemic.

immunology↗

bioRxiv2020

The impact of global and local Polynesian genetic ancestry on complex traits in Native Hawaiians

Epidemiological studies of obesity, Type-2 diabetes (T2D), cardiovascular diseases and several common cancers have revealed an increased risk in Native Hawaiians compared to European- or Asian-Americans living in the Hawaiian islands. However, there remains a gap in our understanding of the genetic factors that affect the health of Native Hawaiians. To fill this gap, we studied the genetic risk factors at both the chromosomal and sub-chromosomal scales using genome-wide SNP array data on [~]4,000 Native Hawaiians from the Multiethnic Cohort. We estimated the genomic proportion of Native Hawaiian ancestry ("global ancestry," which we presumed to be Polynesian in origin), as well as this ancestral component along each chromosome ("local ancestry") and tested their respective association with binary and quantitative cardiometabolic traits. After attempting to adjust for non-genetic covariates evaluated through questionnaires, we found that per 10% increase in global Polynesian genetic ancestry, there is a respective 8.6%, and 11.0% increase in the odds of being diabetic (P = 1.65 10-4) and having heart failure (P = 2.18 10-4), as well as a 0.059 s.d. increase in BMI (P = 1.04 10-10). When testing the association of local Polynesian ancestry with risk of disease or biomarkers, we identified a chr6 region associated with T2D. This association was driven by an uniquely prevalent variant in Polynesian ancestry individuals. However, we could not replicate this finding in an independent Polynesian cohort from Samoa due to the small sample size of the replication cohort. In conclusion, we showed that Polynesian ancestry, which likely capture both genetic and lifestyle risk factors, is associated with an increased risk of obesity, Type-2 diabetes, and heart failure, and that larger cohorts of Polynesian ancestry individuals will be needed to replicate the putative association on chr6 with T2D. Author SummaryNative Hawaiians are one of the fastest growing ethnic minority in the U.S., and exhibit increased risk for metabolic and cardiovascular diseases. However, they are generally understudied, especially from a genetic perspective. To fill this gap, we studied the association of Polynesian genetic ancestry, at genomic and subgenomic scale, with quantitative and binary traits in self-identified Native Hawaiians. We showed that Polynesian ancestry, which likely capture both genetic and non-genetic risk factors related to Native Hawaiian people and culture are associated with increased risk for obesity, type-2 diabetes, and heart failure. While we do not endorse utilizing genetic information to supplant current standards of defining community membership through self-identity or genealogical records, our results suggest future studies could identify population-specific genetic susceptibility factors that may be useful in suggesting underlying biological mechanisms and reducing the disparity in disease interventions in Polynesian populations.

genetics↗

bioRxiv2020

Fusarium verticillioides peroxins associated with peroxisomal docking/translocation module serve important roles in fumonisin biosynthesis and virulence

Peroxisomes are ubiquitous organelles in eukaryotic cells that fulfill various important metabolic functions. In this study, we investigated the role of Docking/Translocation Module (DTM) peroxins, mainly FvPex8, FvPex13, FvPex14, and FvPex33, in Fusarium verticillioides virulence and fumonisin B1 (FB1) biosynthesis. Protein interaction experiments suggested that FvPex13 serves as the core subunit of F. verticillioides DTM. When we generated gene deletion mutants ({Delta}Fvpex8, {Delta}Fvpex13, {Delta}Fvpex14, {Delta}Fvpex33, {Delta}Fvpex33/14) and examined whether the expression of other peroxin genes were affected in the DTM mutants, {Delta}Fvpex8 strain showed most drastic changes to PEX gene expression profiles. Deletion mutants exhibited disparity in carbon source utilization and defect in cell wall integrity when stress agents were applied. Under nutrient starvation, mutants also showed higher levels of lipid droplet accumulation. Notably, {Delta}Fvpex8 mutant showed significant FB1 reduction and altered expression of FUM1 and FUM19 genes. However, FvPex13 was primarily responsible for virulence, while {Delta}Fvpex33/14 double mutant also showed virulence defect. In summary, our study suggests that FvPex13 is the core component of DTM, regulating peroxisome membrane biogenesis as well as PTS1- and PTS2-mediated transmembrane cargo transportation. Importantly, we predict FvPex8 as a key component in DTM that affects peroxisome function in FB1 biosynthesis in F. verticillioides.

microbiology↗