Biology subjects

Taylor, W.

Publications and source records attributed to Taylor, W..

10 recordsLinked to original sources

bioRxiv2025

Emergent self-inhibition governs the landscape of stable states in complex ecosystems

Species-rich ecosystems often exhibit multiple stable states with distinct species compositions. Yet, the factors determining the likelihood of each states occurrence remain poorly understood. Here, we characterize and explain the landscape of stable states in the random Generalized Lotka-Volterra (GLV) model, in which multistability is widespread. We find that the same pool of species with random initial abundances can result in different stable states, whose likelihoods typically differ by orders of magnitude. A states likelihood increases sharply with its total biomass, or inverse self-inhibition. We develop a simplified model to predict and explain this behavior, by coarse-graining ecological interactions so that each stable state behaves as a unit. In this setting, we can accurately predict the entire landscape of stable states using only two macroscopic properties: the biomass of each state and species diversity. Our analyses also provide insight into the biomass-likelihood relationship: High-biomass states have low self-inhibition and thus grow faster, outcompete others, and become much more likely. These results reveal emergent self-inhibition as a fundamental organizing principle for the attractor landscape of complex ecosystems--and provide a path to predict ecosystem outcomes without knowing microscopic interactions.

ecology↗

bioRxiv2024

On the structure of multiple stable equilibria in competitive ecological systems

For some ecological systems with a large pool of possible species, there can be multiple stable equilibria with different species composition. Natural or anthropogenic disruption can induce a shift between different such equilibria. While some work has been done on ecological systems with multiple equilibria, there is no general theory governing the distribution of equilibria or characterizing the basins of attraction of different equilibria. This article addresses these questions in a simple class of Lotka-Volterra models. We focus on competitive systems of species on a niche axis with multiple equilibria. We find that basins of attraction are generally larger for equilibria with greater biomass; in many cases, the basin of attraction size scales roughly exponentially with the net biomass of equilibria. This is illustrated in two ecologically relevant limits. In a continuous limit with species spaced arbitrarily closely on the niche axis, equilibria with different numbers of species provide new perspective on the notion of limiting similarity. In another limit, akin to a statistical mechanical model, the niche axis becomes infinite while the range of interactions remains fixed; in this limit we prove the exponential relation between basin size and biomass using the Markov chain central limit theorem.

ecology↗

bioRxiv2024

Resolving a neonatal intensive care unit outbreak of methicillin-resistant Staphylococcus aureus to the SNV level using Oxford Nanopore simplex reads and HERRO error correction

ObjectivesOur laboratory began prospective genomic surveillance for healthcare-associated organisms in 2022 using Oxford Nanopore Technologies (ONT) sequencing as a standalone platform. This has permitted the early detection of outbreaks but has been insufficient for single-nucleotide variant (SNV)-level analysis due to lower read accuracy than Illumina sequencing. This study aimed to determine whether Haplotype-aware ERRor cOrrection (HERRO) of ONT data could permit high-resolution comparison of outbreak isolates. MethodsWe used ONT simplex reads from isolates involved in a recent outbreak of methicillin-resistant Staphylococcus aureus (MRSA) in our neonatal unit. The raw sequence data were re-basecalled and adapter-trimmed using Dorado v0.7.0. The simplex reads then underwent HERRO correction. The resulting genome assemblies and phylogenies were compared with previous analyses (using Dorado v0.3.4, no HERRO correction and data generated by Illumina sequencing). ResultsFive of nine outbreak isolates were included in the analysis. The remaining four isolates had insufficient read lengths (N50 values <10,000 bp) and did not provide complete chromosome coverage after HERRO correction. The average chromosome sequencing depth for nanopore data was 147x (range: 44-220x) with an average read N50 of 12,215 bp (interquartile range (IQR): 11,439-12,711 bp). The median pairwise SNV distance between outbreak isolates from the original investigation was 51 SNVs (range: 40-68), which decreased to 3 SNVs (range: 1-15) with HERRO correction. Illumina sequencing generated a median SNV distance of 2 (range: 0-13). The resulting standalone ONT HERRO-corrected phylogeny was almost indistinguishable from the standalone Illumina-generated phylogeny. ConclusionsThe addition of HERRO correction meant isolates from this MRSA outbreak could be resolved to a level on par with Illumina sequencing. ONT data following HERRO correction represents a viable standalone option for high-resolution genomic analysis of hospital outbreaks, provided sufficient read lengths can be generated.

genomics↗

bioRxiv2023

TEPEAK : A novel method for identifying and characterizing polymorphic transposable elements in non-model species populations

Transposable elements (TEs) replicate within genomes and are an active source of genetic variability in many species. Their role in immunity and domestication underscores their biological significance. However, analyzing TEs, especially within lesser-studied and wild populations, poses considerable challenges. To address this, we introduce TEPEAK, a simple and efficient approach to identify and characterize TEs in populations without any prior sequence or loci information. In addition to processing user-submitted genomes, TEPEAK integrates with the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) to increase cohort sizes or incorporate proximate species. Our application of TEPEAK to 256 horse genomes spanning 11 groups reaffirmed established genetic histories and highlighted disruptions in crucial genes. Some identified TEs were also detectable in species closely related to horses. TEPEAK paves the way for comprehensive genetic variation analysis in traditionally understudied populations by simplifying TE studies. TEPEAK is open-source and freely available at https://github.com/mrburke00/TEPEAK.

bioinformatics↗

bioRxiv2023

Integrating coexistence and invasion theories under a probabilistic framework

The dynamics of ecological communities in nature are typically characterized by probabilistic processes involving invasion dynamics. Because of technical challenges, however, the majority of theoretical and experimental studies have focused on coexistence dynamics. Therefore, it has become central to understand the extent to which coexistence outcomes can be used to predict analogous invasion outcomes relevant to systems in nature. Here, we study the limits to this predictability under a geometric and probabilistic Lotka-Volterra framework. We show that while survival probability in coexistence dynamics can be fairly closely translated into colonization probability in invasion dynamics, the translation is less precise between community persistence and community augmentation, and worse between exclusion probability and replacement probability. These results provide a guiding and testable theoretical framework regarding the translatability of outcomes between coexistence and invasion outcomes when communities are represented by Lotka-Volterra dynamics under environmental uncertainty.

ecology↗

bioRxiv2022

Understanding the variability of pairwise coexistence within multispecies systems

The persistence of virtually every single species depends on both the presence of other species and the specific environmental conditions in a given location. Because in natural settings many of these conditions are unknown, research has been centered on finding the fraction of possible conditions (probability) leading to species coexistence. The focus has been on the persistence probability of an entire multispecies community (formed of either two or more species). However, the methodological and philosophical question has always been whether we can observe the entire community and, if not, what the conditions are under which an observed subset of the community can persist as part of a larger multispecies system. Here, we derive long-term (using analytical calculations) and short-term (using simulations and experimental data) system-level indicators of the effect of third-party species on the coexistence probability of a pair (or subset) of species under unknown environmental conditions. We demonstrate that the fraction of conditions incompatible with the possible coexistence of a pair of species tends to become vanishingly small within systems of increasing numbers of species. Yet, the probability of pairwise coexistence in isolation remains approximately the expected probability of pairwise coexistence in more diverse assemblages. In addition, we found that when third-party species tend to reduce (resp. increase) the coexistence probability of a pair, they tend to exhibit slower (resp. faster) rates of competitive exclusion. Long-term and short-term effects of the remaining third-party species on all possible specific pairs in a system are not equally distributed, but these differences can be mapped and anticipated under environmental uncertainty. Author SummaryIt is debated whether the frequency with which two species coexist in isolation or within a single environmental context is representative of their coexistence expectation within larger multispecies systems and across different environmental conditions. Here, using analytical calculations, simulations, and experimental data, we show why and how third-party species can provide the opportunity for pairwise coexistence regardless of whether a pair of species can coexist in isolation across different environmental conditions. However, we show that this opportunity is not homogeneously granted across all pairs within the same system. We provide a framework to understand and map the long-term and short-term effects that third-party species have on the coexistence of each possible subset in a multispecies system.

ecology↗

bioRxiv2021

THE SPLICING FACTOR PTBP1 REPRESSES TP63 γ ISOFORM PRODUCTION IN SQUAMOUS CELL CARCINOMA

The TP63 gene encodes the transcription factor p63. It is frequently amplified or overexpressed in squamous cell carcinomas. Owing to alternative splicing, p63 has multiple isoforms called , {beta}, {gamma} and {delta}. The regulatory functions of p63 may be isoform-specific. The isoform inhibits the epithelial to mesenchymal transition (EMT) and controls apoptosis, while the {gamma} isoform promotes EMT. Here, we observed in TCGA data that a high ratio of the TP63{gamma} isoform to the other isoforms is a pejorative factor for the survival of patients with head and neck squamous cell carcinoma (HNSCC). We therefore addressed the regulation of the {gamma} isoform. In several tissues (GTEX data), the expression of the RNA-binding protein PTBP1 (polypyrimidine tract binding protein 1) is negatively correlated with the abundance of TP63{gamma}. Accordingly, we demonstrated that PTBP1 depletion in HNSCC cell lines leads to an increase in abundance of the {gamma} isoform. By RNA immunoprecipitation and in vitro interaction assays, we showed that PTBP1 directly binds to TP63 pre-mRNA in close proximity to the TP63{gamma}-specific exon. The region around the TP63{gamma}-specific exon was sufficient to elicit a PTBP1-dependent regulation of alternative splicing in a splice reporter minigene assay. Finally, we demonstrated that the regulation of TP63{gamma} production by PTBP1 is conserved in amphibians, revealing that it encounters a strong evolutionary pressure. Together, these results identify TP63{gamma} as a prognostic marker in HNSCC, and identify PTBP1 as a direct negative regulator of its production.

cancer biology↗

bioRxiv2020

A Single Dose of Self-Transcribing and Replicating RNA Based SARS-CoV-2 Vaccine Produces Protective Adaptive Immunity In Mice

A self-transcribing and replicating RNA (STARR) based vaccine (LUNAR(R)-COV19) has been developed to prevent SARS-CoV-2 infection. The vaccine encodes an alphavirus-based replicon and the SARS-CoV-2 full length spike glycoprotein. Translation of the replicon produces a replicase complex that amplifies and prolong SARS-CoV-2 spike glycoprotein expression. A single prime vaccination in mice led to robust antibody responses, with neutralizing antibody titers increasing up to day 60. Activation of cell mediated immunity produced a strong viral antigen specific CD8+ T lymphocyte response. Assaying for intracellular cytokine staining for IFN-{gamma} and IL-4 positive CD4+ T helper lymphocytes as well as anti-spike glycoprotein IgG2a/IgG1 ratios supported a strong Th1 dominant immune response. Finally, single LUNAR-COV19 vaccination at both 2 g and 10 g doses completely protected human ACE2 transgenic mice from both mortality and even measurable infection following wild-type SARS-CoV-2 challenge. Our findings collectively suggest the potential of Lunar-COV19 as a single dose vaccine.

immunology↗

bioRxiv2019

Chronic circadian disruption modulates breast cancer cell stemness and their immune microenvironment to drive metastasis in mice

Breast cancer is the most common type and one of the major causes of cancer death in woman worldwide. Epidemiological studies have established a link between night shift work and increased cancer risk, suggesting that circadian disruption may interfere with carcinogenesis. We aim to shed light on the effect of chronic jetlag on mammary tumour development. Therefore, we used a mouse model of spontaneous mammary tumorigenesis that we exposed to chronic circadian disruption. We observed that circadian disruption significantly increases cancer cell dissemination and metastasis. It also enhances the stemness and tumour-initiating potential of tumour cells and creates an immunosuppressive shift in the tumour microenvironment. We finally showed that all these defects can be corrected by the use of a CXCR2 inhibitor. Altogether, our data provide a conceptual framework to better understand and manage the effects of chronic circadian disruption on breast cancer progression.

cancer biology↗

bioRxiv2019

MinION Sequencing of colorectal cancer tumour microbiomes - a comparison with amplicon-based and RNA-Sequencing

Recent evidence suggests a role for the gut microbiome in the development and progression of colorectal cancer. In this study we compare MinION sequencing with meta-transcriptomics and amplicon-based sequencing for microbiome analysis of colorectal tumour tissue samples. DNA and RNA were extracted from 11 colorectal tumour samples. RNA-Sequencing, 16S rRNA amplicon sequencing and MinION genomic sequencing was carried out and resulting data used as input for taxonomic classification using Kraken2. Taxonomic concordance between the three platforms at different taxonomic levels was tested on a per sample basis. The average number of reads per sample using RNA-Sequencing was more than 129 times that generated using MinION sequencing. However, the average read length of MinION sequences was more than 13 times that of RNA or 16S rRNA amplicon sequencing. 16S sequencing was less informative beyond the genus level, and both RNA-Sequencing and MinION sequencing could detect more phyla and genera in the same samples, compared to 16S sequencing. Long-read sequences generated using MinION sequencing can compensate for low numbers of reads for bacterial classification. MinION sequencing can discriminate between bacterial strains and plasmids and shows potential as a tool for microbiome sequencing of colorectal cancers in a clinical setting.

microbiology↗