Biology subjects

Gu, Q.

Publications and source records attributed to Gu, Q..

At least 55 records · Page 3Linked to original sources

bioRxiv2022

Timing and magnitude of the type-I interferon response are determinants of disease tolerance in arbovirus infection

Infected hosts possess two alternative strategies to protect themselves against the negative impact of virus infections: (i) "resistance", directed to abrogate virus replication, or (ii) "disease tolerance", aimed to avoid organ and tissue damage without overly controlling viral burden. The overall principles governing pathogen resistance are well understood, while less is known about those involved in disease tolerance. Here, we studied bluetongue virus (BTV), the cause of a major disease of ruminants, bluetongue, as a model system to investigate the mechanisms of disease tolerance. BTV induces clinical disease mainly in sheep, while cattle are considered reservoirs of infection, rarely exhibiting clinical symptoms despite sustained viremia. Here, we show that BTV consistently reaches higher titres in ovine primary cells, compared to cells derived from cattle. The variable replication kinetics of BTV in sheep and cattle cells were mostly abolished by abrogating the cell type-I interferon (IFN) response. By screening a library of bovine interferon stimulated genes (ISGs), we identified restriction factors blocking BTV replication, however both sheep and cattle orthologues of these antiviral genes possess anti-BTV properties. Importantly, we demonstrate that BTV induces a faster host cell protein synthesis shutoff in primary sheep cells, compared to cattle cells, which results in an earlier downregulation of antiviral proteins. Moreover, by RNAseq we also show a more pronounced expression of ISGs in BTV infected cattle cells compared to sheep cells. Our data provide a new perspective on how the type-I IFN response in reservoir species can have overall positive effects on both virus and host evolution.

microbiology↗

bioRxiv2022

Imprinted SARS-CoV-2 humoral immunity induces converging Omicron RBD evolution

Continuous evolution of Omicron has led to a rapid and simultaneous emergence of numerous variants that display growth advantages over BA. 5. Despite their divergent evolutionary courses, mutations on their receptor-binding domain (RBD) converge on several hotspots. The driving force and destination of such convergent evolution and its impact on humoral immunity remain unclear. Here, we demonstrate that these convergent mutations can cause striking evasion of neutralizing antibody (NAb) drugs and convalescent plasma, including those from BA.5 breakthrough infection, while maintaining sufficient ACE2 binding capability. BQ.1.1.10, BA.4.6.3, XBB, and CH. 1.1 are the most antibody-evasive strain tested, even exceeding SARS-CoV-1 level. To delineate the origin of the convergent evolution, we determined the escape mutation profiles and neutralization activity of monoclonal antibodies (mAbs) isolated from BA.2 and BA.5 breakthrough-infection convalescents. Importantly, due to humoral immune imprinting, BA.2 and especially BA.5 breakthrough infection caused significant reductions in the epitope diversity of NAbs and increased proportion of non-neutralizing mAbs, which in turn concentrated humoral immune pressure and promoted convergent evolution. Moreover, we showed that the convergent RBD mutations could be accurately inferred by integrated deep mutational scanning (DMS) profiles, and the evolution trends of BA.2.75/BA.5 subvariants could be well-simulated through constructed convergent pseudovirus mutants. Together, our results suggest current herd immunity and BA.5 vaccine boosters may not provide good protection against infection. Broad-spectrum SARS-CoV-2 vaccines and NAb drugs development should be highly prioritized, and the constructed mutants could help to examine their effectiveness in advance.

immunology↗

bioRxiv2022

A Web-based Software Resource for Interactive Analysis of Multiplex Tissue Imaging Datasets

Highly multiplexed tissue imaging (MTI) are powerful spatial proteomics technologies that enable in situ single-cell characterization of tissues. However, analysis and visualization of MTI datasets remains challenging, and we developed the Galaxy-ME software hub to address this challenge. Galaxy-ME is a web-based, interactive software hub that enables end-to-end analysis and visualization of MTI datasets and is accessible to everyone. To demonstrate its utility, Galaxy-ME was used to analyze datasets obtained from multiple MTI assays in both normal and cancerous tissues. Galaxy-ME is a publicly available web resource.

bioinformatics↗

bioRxiv2022

Rational identification of potent and broad sarbecovirus-neutralizing antibody cocktails from SARS convalescents

SARS-CoV-2 Omicron sublineages have escaped most RBD-targeting therapeutic neutralizing antibodies (NAbs), which proves the previous NAb drug screening strategies deficient against the fast-evolving SARS-CoV-2. Better broad NAb drug candidate selection methods are needed. Here, we describe a rational approach for identifying RBD-targeting broad SARS-CoV-2 NAb cocktails. Based on high-throughput epitope determination, we propose that broad NAb drugs should target non-immunodominant RBD epitopes to avoid herd immunity-directed escape mutations. Also, their interacting antigen residues should focus on sarbecovirus conserved sites and associate with critical viral functions, making the antibody-escaping mutations less likely to appear. Following the criteria, a featured non-competing antibody cocktail, SA55+SA58, is identified from a large collection of broad sarbecovirus NAbs isolated from SARS convalescents. SA55+SA58 potently neutralizes ACE2-utilizing sarbecoviruses, including circulating Omicron variants, and could serve as broad SARS-CoV-2 prophylactics to offer long-term protection. Our screening strategy can also be applied to identify broad-spectrum NAb drugs against other fast-evolving viruses, such as influenza viruses.

immunology↗

bioRxiv2022

Neutralizing antibody evasion and receptor binding features of SARS-CoV-2 Omicron BA.2.75

Recently emerged SARS-CoV-2 Omicron subvariant, BA.2.75, displayed a local growth advantage over BA.2.38, BA.2.76 and BA.5 in India. The underlying mechanism of BA.2.75s enhanced infectivity, especially compared to BA.5, remains unclear. Here, we show that BA.2.75 exhibits substantially higher ACE2-binding affinity than BA.5. Also, BA.2.75 spike shows decreased thermostability and increased "up" RBD conformation in acidic conditions, suggesting enhanced low-pH-endosomal cell-entry pathway utilization. BA.2.75 is less humoral immune evasive than BA.4/BA.5 in BA.1/BA.2 breakthrough-infection convalescents; however, BA.2.75 shows heavier neutralization evasion in Delta breakthrough-infection convalescents. Importantly, plasma from BA.5 breakthrough infection exhibit significantly weaker neutralization against BA.2.75 than BA.5, mainly due to BA.2.75s distinct RBD and NTD-targeting antibody escaping pattern from BA.4/BA.5. Additionally, Evusheld and Bebtelovimab remain effective against BA.2.75, and Sotrovimab recovered RBD-binding affinity. Together, our results suggest BA.2.75 may prevail after the global BA.4/BA.5 wave, and its increased receptor-binding capability could allow further incorporation of immune-evasive mutations.

immunology↗

bioRxiv2022

Zoonotic avian influenza viruses evade human BTN3A3 restriction

Cross-species transmission of avian influenza A viruses (IAVs) into humans could represent the first step of a future pandemic1. Multiple factors limiting the spillover and adaptation of avian IAVs in humans have been identified, but they are not sufficient to explain which virus lineages are more likely to cross the species barrier1,2. Here, we identified human BTN3A33 (butyrophilin subfamily 3 member A3) as a potent inhibitor of avian but not human IAVs. We determined that BTN3A3 is constitutively expressed in human airways and its antiviral activity evolved in primates. We show that BTN3A3 restriction acts at the early stages of virus replication by inhibiting avian IAV vRNA transcription. We identified residue 313 in the viral nucleoprotein (NP) as the genetic determinant of BTN3A3 sensitivity (313F, or rarely 313L in avian viruses) or evasion (313Y or 313V in human viruses). However, several serotypes of avian IAVs that spilled over into humans in recent decades evade BTN3A3 restriction. In these cases, BTN3A3 evasion is due to substitutions (N, H or Q) in NP residue 52 that is adjacent to residue 313 in the NP structure4. Importantly, we identified more than 150 avian IAV lineages with a BTN3A3-resistant genotype. In conclusion, sensitivity or resistance to BTN3A3 is another factor to consider in the risk assessment of the zoonotic potential of avian influenza viruses.

microbiology↗

bioRxiv2022

BA.2.12.1, BA.4 and BA.5 escape antibodies elicited by Omicron infection

SARS-CoV-2 Omicron sublineages BA.2.12.1, BA.4 and BA.5 exhibit higher transmissibility over BA.21. The new variants receptor binding and immune evasion capability require immediate investigation. Here, coupled with Spike structural comparisons, we show that BA.2.12.1 and BA.4/BA.5 exhibit comparable ACE2-binding affinities to BA.2. Importantly, BA.2.12.1 and BA.4/BA.5 display stronger neutralization evasion than BA.2 against the plasma from 3-dose vaccination and, most strikingly, from post-vaccination BA.1 infections. To delineate the underlying antibody evasion mechanism, we determined the escaping mutation profiles2, epitope distribution3 and Omicron neutralization efficacy of 1640 RBD-directed neutralizing antibodies (NAbs), including 614 isolated from BA.1 convalescents. Interestingly, post-vaccination BA.1 infection mainly recalls wildtype-induced humoral memory. The resulting elicited antibodies could neutralize both wildtype and BA.1 and are enriched on non-ACE2-competing epitopes. However, most of these cross-reactive NAbs are heavily escaped by L452Q, L452R and F486V. BA.1 infection can also induce new clones of BA.1-specific antibodies that potently neutralize BA.1; nevertheless, these NAbs are largely escaped by BA.2/BA.4/BA.5 due to D405N and F486V, and react weakly to pre-Omicron variants, exhibiting poor neutralization breadths. As for therapeutic NAbs, Bebtelovimab4 and Cilgavimab5 can effectively neutralize BA.2.12.1 and BA.4/BA.5, while the S371F, D405N and R408S mutations would undermine most broad sarbecovirus NAbs. Together, our results indicate that Omicron may evolve mutations to evade the humoral immunity elicited by BA.1 infection, suggesting that BA.1-derived vaccine boosters may not achieve broad-spectrum protection against new Omicron variants.

immunology↗

bioRxiv2022

Comprehensive Epitope Mapping of Broad Sarbecovirus Neutralizing Antibodies

Omicron sub-lineage BA.2 has rapidly surged globally, accounting for over 60% of recent SARS-CoV-2 infections. Newly acquired RBD mutations and high transmission advantage over BA.1 urge the investigation of BA.2s immune evasion capability. Here, we show that BA.2 causes strong neutralization resistance, comparable to BA.1, in vaccinated individuals plasma. However, BA.2 displays more severe antibody evasion in BA.1 convalescents, and most prominently, in vaccinated SARS convalescents plasma, suggesting a substantial antigenicity difference between BA.2 and BA.1. To specify, we determined the escaping mutation profiles1,2 of 714 SARS-CoV-2 RBD neutralizing antibodies, including 241 broad sarbecovirus neutralizing antibodies isolated from SARS convalescents, and measured their neutralization efficacy against BA.1, BA.1.1, BA.2. Importantly, BA.2 specifically induces large-scale escape of BA.1/BA.1.1-effective broad sarbecovirus neutralizing antibodies via novel mutations T376A, D405N, and R408S. These sites were highly conserved across sarbecoviruses, suggesting that Omicron BA.2 arose from immune pressure selection instead of zoonotic spillover. Moreover, BA.2 reduces the efficacy of S309 (Sotrovimab)3,4 and broad sarbecovirus neutralizing antibodies targeting the similar epitope region, including BD55-5840. Structural comparisons of BD55-5840 in complexes with BA.1 and BA.2 spike suggest that BA.2 could hinder antibody binding through S371F-induced N343-glycan displacement. Intriguingly, the absence of G446S mutation in BA.2 enabled a proportion of 440-449 linear epitope targeting antibodies to retain neutralizing efficacy, including COV2-2130 (Cilgavimab)5. Together, we showed that BA.2 exhibits distinct antigenicity compared to BA.1 and provided a comprehensive profile of SARS-CoV-2 antibody escaping mutations. Our study offers critical insights into the humoral immune evading mechanism of current and future variants.

immunology↗

bioRxiv2021

Defining the Characteristics of Type I Interferon Stimulated Genes: Insight from Expression Data and Machine Learning

A virus-infected cell triggers a signalling cascade resulting in the secretion of interferons (IFNs), which in turn induce the up-regulation of IFN-stimulated genes (ISGs) that play an important role in the inhibition of the viral infection and the return to cellular homeostasis. Here, we conduct detailed analyses on 7443 features relating to evolutionary conservation, nucleotide composition, gene expression, amino acid composition, and network properties to elucidate factors associated with the stimulation of genes in response to type I IFNs. Our results show that ISGs are less evolutionary conserved than genes that are not significantly stimulated in IFN experiments (non-ISGs). ISGs show significant depletion of GC-content in the coding region of their canonical transcripts, which leads to under-representation in the nucleotide compositions. Differences between ISGs and non-ISGs are also reflected in the properties of their coded amino acid sequence compositions. Network analyses show that ISG products tend to be involved in key paths but are away from hubs or bottlenecks of the human protein-protein interaction (PPI) network. Our analyses also show that interferon-repressed human genes (IRGs), which are down-regulated in the presence of IFNs, can have similar properties to ISGs, thus leading to false positives in ISG predictions. Based on these analyses, we design a machine learning framework integrating the usage of support vector machine (SVM) and feature selection algorithms. The ISG prediction achieves an area under the receiver operating characteristic curve (AUC) of 0.7455 and demonstrates the similarity between ISGs triggered by type I and III IFNs. Our machine learning model predicts a number of genes as potential ISGs that so far have shown no significant differential expression when stimulated with IFN in the cell types and tissue types compiled in the available IFN-related databases. A webserver implementing our method is accessible at http://isgpre.cvr.gla.ac.uk/. Author summaryInterferons (IFNs) are signalling proteins secreted from host cells. IFN-triggered signalling activates the host immune system in response to intra-cellular infection. It results in the stimulation of many genes that have anti-pathogen roles in host defenses. Interferon-stimulated genes (ISGs) have unique properties that make them different from those not significantly up-regulated in response to IFNs (non-ISGs). We find the down-regulated interferon-repressed genes (IRGs) have some shared properties with ISGs. This increases the difficulty of distinguishing ISGs from non-ISGs. The use of machine learning is a sensible strategy to provide high throughput classifications of putative ISGs, for investigation with in vivo or in vitro experiments. Machine learning can also be applied to human genes for which there are insufficient expression levels before and after IFN treatment in various experiments. Additionally, the interferon type has some impact on ISG predictability. We expect that our study will provide new insight into better understanding the inherent characteristics of human genes that are related to response in the presence of IFNs.

immunology↗

bioRxiv2021

Botrytis cinerea BcPTP1 is a late infection phase, cysteine rich protein cytotoxic effector

Botrytis cinerea is a broad-host-range necrotrophic phytopathogen responsible for serious crops diseases. To facilitate infection, B. cinerea secretes a large number of effectors that induce plant cell death. In screening secretome data of B. cinerea during infection stage, we identified a phytotoxic protein (BcPTP1) that can also induce immune resistance in plants. BcPTP1 is a small (90 aa), cysteine rich protein without any known domains. Transiently expression of BcPTP1 in leaves caused chlorosis that intensifies with time and eventually lead to cell death. Point mutations in eight of the 10 cysteine residues of BcPTP1 abolished the toxic effect, however residual toxic activity remained after heating the peptide, suggesting contribution of unknown epitopes to protein phytotoxic effect. The transcript level of the bcptp1 gene was low during the first 36 h after inoculation and increased sharply upon transition to the late infection stage, suggesting a role of BcPTP1 in lesion spreading. While statistically insignificant, deletion of the bcptp1 gene led to slightly smaller lesions on bean leaves. Further analyses indicated that BcPTP1 is internalized into plant cells after secreting into the apoplast and its phytotoxic effect is negatively regulated by the receptor-like kinases BAK1 and SOBIR1. Collectively, our findings show that BcPTP1 is a virulence factor that toxifies the host cells and facilitates lesion spreading during the late infection stage.

pathology↗

bioRxiv2021

WDR82-binding long non-coding RNA lncEry controls mouse erythroid differentiation and maturation

Hematopoietic differentiation is controlled by both genetic and epigenetic regulators. Long non-coding RNAs (lncRNAs) have been demonstrated to be important for normal hematopoiesis, but their function in erythropoiesis needs to be further explored. We profiled the transcriptomes of 16 murine hematopoietic cell populations by deep RNA-sequencing and identified a novel lncRNA, Gm15915, that was highly expressed in erythroid-related progenitors and erythrocytes. For this reason, we named it lncEry. We also identified a novel lncEry isoform, which was also the principal transcript that has not been reported before. LncEry depletion impaired erythropoiesis, indicating the important role of the lncRNA in regulating erythroid differentiation and maturation. Mechanistically, we found that lncEry interacted with WD repeat-containing protein 82 (WDR82) to promote the transcription of Klf1 and globin genes and thus control the early and late stages of erythropoiesis, respectively. These findings identified lncEry as an important player in the transcriptional regulation of erythropoiesis.

cell biology↗

bioRxiv2021

Using Progressive Context Encoders for Anomaly Detection in Digital Pathology Images

Whole slide imaging (WSI) is transforming the practice of pathology, converting a qualitative discipline into a quantitative one. However, one must exercise caution in interpreting algorithm assertions, particularly in pathology where an incorrect classification could have profound impacts on a patient, and rare classes exist that may not have been seen by the algorithm during training. A more robust approach would be to identify areas of an image for which the pathologist should concentrate their effort to make a final diagnosis. This anomaly detection strategy would be ideal for WSI, but given the extremely high resolution and large file sizes, such an approach is difficult. Here, we combine progressive generative adversarial networks with a flexible adversarial autoencoder architecture capable of learning the "normal distribution" of WSIs of normal skin tissue at extremely high resolution and demonstrate its anomaly detection performance. Our approach yielded pixel-level accuracy of 89% for identifying melanoma, suggesting that our label-free anomaly detection pipeline is a viable strategy for generating high quality annotations - without tedious manual segmentation by pathologists. The code is publicly available at https://github.com/Steven-N-Hart/P-CEAD.

pathology↗

bioRxiv2021

A novel method for generating 3D constructs with branched vascular networks using multi-materials bioprinting and direct surgical anastomosis

Vessels pervade almost all body tissues, and significantly influence the pathophysiology of human body. Previous attempts to establish multi-scale vascular connection and function in 3D model tissues using bioprinting have had limited success due to the incoordination between cell-laden materials and stability of the perfusion channel. Here, we report a methodology to fabricate centimetre-scale vascularized soft tissue with high viability and accuracy using multi-materials bioprinting involving inks with low viscosity and a customized multistage-temperature-control printer. The tissue formed was perfused with branched vasculature with well-formed 3D capillary network and lumen, which would potentially supply the cellular components with sufficient nutrients in the matrix. Furthermore, the same methodology was applied for generating liver-like tissue with the objective to fabricate and mimic a mature and functional liver tissue, with increased functionality in terms of synthesis of liver specific proteins after in vitro perfusion and in vivo subperitoneal transplantation in mice. Moreover, to establish immediate blood perfusion, an elastic layer was printed wrapping sacrificial ink to support the direct surgical anastomosis of the carotid artery to the jugular vein. Our findings highlight the support extended by vasculature network in soft hydrogels which helps to sustain the thick and dense cellularization in engineered tissues.

bioengineering↗

bioRxiv2020

Meta-analysis of virus-induced host gene expression reveals unique signatures of immune dysregulation induced by SARS-CoV-2

The clinical outcome of COVID-19 has an extreme age, genetic and comorbidity bias that is thought to be driven by an impaired immune response to SARS-CoV-2, the causative agent of the disease. The unprecedented impact of COVID-19 on global health has resulted in multiple studies generating extensive gene expression datasets in a relatively short period of time. In order to better understand the immune dysregulation induced by SARS-CoV-2, we carried out a meta-analysis of these transcriptomics data available in the published literature. Datasets included both those available from SARS-CoV-2 infected cell lines in vitro and those from patient samples. We focused our analysis on the identification of viral perturbed host functions as captured by co-expressed gene module analysis. Transcriptomics data from lung biopsies and nasopharyngeal samples, as opposed to those available from other clinical samples and infected cell lines, provided key signatures on the role of the hosts immune response on COVID-19 pathogenesis. For example, severity of infection and patients age are linked to the absence of stimulation of the RIG-I-like receptor signaling pathway, a known critical immediate line of defense against RNA viral infections that triggers type-I interferon responses. In addition, co-expression analysis of age-stratified transcriptional data provided evidence that signatures of key immune response pathways are perturbed in older COVID-19 patients. In particular, dysregulation of antigen-presenting components, down-regulation of cell cycle mechanisms and signatures of hyper-enriched monocytes were strongly correlated with the age of older individuals infected with SARS-CoV-2. Collectively, our meta-analysis highlights the ability of transcriptomics and gene-module analysis of aggregated datasets to aid our improved understanding of the host-specific disease mechanisms underpinning COVID-19.

bioinformatics↗

bioRxiv2020

Elevated temperature inhibits SARS-CoV-2 replication in respiratory epithelium independently of the induction of IFN-mediated innate immune defences

The pandemic spread of SARS-CoV-2, the etiological agent of COVID-19, represents a significant and ongoing international health crisis. A key symptom of SARS-CoV-2 infection is the onset of fever, with a hyperthermic temperature range of 38 to 41{degrees}C. Fever is an evolutionarily conserved host response to microbial infection and inflammation that can influence the outcome of viral pathogenicity and regulation of host innate and adaptive immune responses. However, it remains to be determined what effect elevated temperature has on SARS-CoV-2 tropism and replication. Utilizing a 3D air-liquid interface (ALI) model that closely mimics the natural tissue physiology and cellular tropism of SARS-CoV-2 infection in the respiratory airway, we identify tissue temperature to play an important role in the regulation of SARS-CoV-2 infection. We show that temperature elevation induces wide-spread transcriptome changes that impact upon the regulation of multiple pathways, including epigenetic regulation and lncRNA expression, without disruption of general cellular transcription or the induction of interferon (IFN)-mediated antiviral immune defences. Respiratory tissue incubated at temperatures >37{degrees}C remained permissive to SARS-CoV-2 infection but severely restricted the initiation of viral transcription, leading to significantly reduced levels of intraepithelial viral RNA accumulation and apical shedding of infectious virus. To our knowledge, we present the first evidence that febrile temperatures associated with COVID-19 inhibit SARS-CoV-2 replication. Our data identify an important role for temperature elevation in the epithelial restriction of SARS-CoV-2 that occurs independently of the induction of canonical IFN-mediated antiviral immune defences and interferon-stimulated gene (ISG) expression.

microbiology↗

bioRxiv2020

AIBP-CAV1-VEGFR3 axis dictates lymphatic cell fateand controls lymphangiogenesis

The lymphatics are essential for the maintenance of tissue fluid homeostasis. Accordingly, lymphatic dysfunction contributes to lymphedema. In development, lymphangiogenesis often requires lymphatic endothelial cell (LEC) lineage specification from the venous ECs and subsequent LEC proliferation and migration, all of which are regulated by the VEGFC/VEGFR3 signaling. Cholesterol is essential for proper cell functions and organ development, yet the molecular mechanism by which cholesterol metabolism controls lymphangiogenesis is unknown. We show that the secreted protein, ApoA1 binding protein (AIBP), dictates lymphatic vessel formation by accelerating cholesterol efflux. Loss of Aibp2, the human paralog in zebrafish, impairs LEC progenitor specification and impedes lymphangiogenesis. Mechanistically, we found that caveolin-1 (CAV-1) suppresses VEGFR3 activation in LECs, and that AIBP-regulated cholesterol efflux disrupts lipid rafts/caveolae and reduces CAV-1 bioavailability, which abolishes the CAV-1 inhibition of VEGFR3 signaling, thereby augmenting VEGFR3 activation and increasing lymphangiogenesis. Enhancement of cholesterol efflux with ApoA1 overexpression or inhibition of cholesterol biosynthesis using atorvastatin restores proper lymphangiogenesis in Aibp2 mutant zebrafish. Loss of Cav-1 increases LEC progenitor specification in zebrafish, and rescues lymphangiogenesis in Aibp2-deficient animals. Recombinant AIBP supplement confers profound LEC fate commitment in the mouse embryonic stem cells (mESC) to LEC differentiation model. Furthermore, enhancement of AIBP-CAV-1-VEGFR3 signaling axis promotes VEGFC-engaged adult lymphangiogenesis in mice. Consistent with these data, AIBP expression is reduced in the epidermis of human lymphedematous skin. These studies identify that AIBP-mediated cholesterol efflux is a critical contributor for lymphangiogenesis. Our studies will provide a new therapeutic avenue for the treatment of lymphatic dysfunctions. One Sentence SummaryOur studies identify that AIBP-CAV-1-VEGFR3 axis enhances VEGFC-elicited lymphangiogenesis, which will guide a new therapeutic strategy for the treatment of lymphatic dysfunctions.

developmental biology↗

bioRxiv2020

Accessible, Reproducible, and Scalable Machine Learning for Biomedicine

Supervised machine learning, where the goal is to predict labels of new instances by training on labeled data, has become an essential tool in biomedical data analysis. To make supervised machine learning more accessible to biomedical scientists, we have developed Galaxy-ML, a platform that enables scientists to perform end-to-end reproducible machine learning analyses at large scale using only a web browser. Galaxy-ML extends Galaxy, a biomedical computational workbench used by tens of thousands of scientists across the world, with a machine learning tool suite that supports end-to-end analysis.

bioinformatics↗

bioRxiv2020

BingleSeq: A user-friendly R package for Bulk and Single-cell RNA-Seq Data Analysis

RNA sequencing is a high-throughput sequencing technique considered as an indispensable research tool used in a broad range of transcriptome analysis studies. The most common application of RNA Sequencing is Differential Expression analysis and it is used to determine genetic loci with distinct expression across different conditions. On the other hand, an emerging field called single-cell RNA sequencing is used for transcriptome profiling at the individual cell level. The standard protocols for both these types of analyses include the processing of sequencing libraries and result in the generation of count matrices. An obstacle to these analyses and the acquisition of meaningful results is that both require programming expertise. BingleSeq was developed as an intuitive application that provides a user-friendly solution for the analysis of count matrices produced by both Bulk and Single-cell RNA-Seq experiments. This was achieved by building an interactive dashboard-like user interface and incorporating three state-of-the-art software packages for each type of the aforementioned analyses, alongside additional features such as key visualisation techniques, functional gene annotation analysis and rank-based consensus for differential gene analysis results, among others. As a result, BingleSeq puts the best and most widely used packages and tools for RNA-Seq analyses at the fingertips of biologists with no programming experience.

bioinformatics↗