Biology subjects

Teixeira, D.

Publications and source records attributed to Teixeira, D..

7 recordsLinked to original sources

bioRxiv2025

Characterization of chemotaxis in soybean symbiont Bradyrhizobium diazoefficiens

ABSTRACTSymbiotic relationships between nitrogen-fixing soil bacteria and legumes provide nearly half of all biologically fixed nitrogen on Earth, playing a crucial role in sustainable agriculture. These relationships rely on bacterial navigation of complex, dynamic soil environments to reach their plant hosts. Central to this behavior are bacterial motility and chemotaxis, the ability to sense and move toward host-derived signals in the rhizosphere. In the soybean symbiont Bradyrhizobium diazoefficiens USDA110, motility is controlled by dual flagellar systems, and this strain contains three putative but uncharacterized chemotaxis operons (che1, che2, and che3). Using targeted deletions of all three predicted cheA genes, we show that cheA2 is the primary driver of chemotaxis toward soybean seed exudate in soft agar assays, and that the greater contribution of cheA2 vs. cheA1 in soft agar chemotaxis is due to its genomic context. Interestingly, we also found that B. diazoefficiens mutants that are incapable of chemotaxis in semisolid media retain wild type-like swimming speeds in aqueous media. These findings provide insight into how the agricultural inoculant B. diazoefficiens coordinates its chemosensory systems to respond to its host plant. IMPORTANCEChemotaxis is crucial for the establishment of beneficial plant-microbe associations, yet mechanistic studies of chemotaxis have been limited to a handful of soil bacterial models, namely Azospirillum brasilense, Sinorhizobium meliloti, and Rhizobium leguminosarum. These three models represent only a fraction of the diversity found among plant- beneficial bacteria and agricultural inoculants. The soybean symbiont Bradyrhizobium diazoefficiens USDA110 is a commonly used soybean inoculant with exceptional nitrogen fixation efficiency, but the genetic control of chemotaxis in B. diazoefficiens has not been examined. Establishing B. diazoefficiens as a model of chemotaxis provides an opportunity to understand how multiple chemotaxis systems coordinate root colonization in this major agricultural symbiont and can enable comparative analyses of plant-microbe recognition strategies across agricultural bacteria.

microbiology↗

bioRxiv2025

Annexin A1 as a key modulator of lung inflammation during coronavirus infections

Exacerbated inflammation is a major contributor to tissue damage and mortality in infectious diseases, including SARS-CoV-2. The resolution phase of inflammation is critical for restoring tissue homeostasis following an injury. Annexin A1 (AnxA1) is a ubiquitous protein that plays a fundamental role in the resolution of inflammation, including in preclinical models of infectious disease. Here, we investigated the role of AnxA1 in coronavirus infection and its potential as a host-targeted therapeutic strategy against SARS-CoV-2. Wild-type (WT) and AnxA1 knockout (AnxA1KO) mice were intranasally infected with the murine betacoronavirus MHV-3 to study the endogenous role of AnxA1. Immunohistochemistry and Western blot analyses in the lungs of MHV-3-infected mice revealed increased AnxA1 expression and its cleavage, which was associated with neutrophilic infiltration (Ly6G+ cells) mainly in peribronchiolar and perivascular regions. AnxA1-deficient mice exhibited higher neutrophilic infiltration and lung damage, alongside increased CXCL1 production in the lungs, when compared to WT-infected mice. In a murine model of SARS-CoV-2 infection in K18-hACE2 mice, we found increased AnxA1 cleavage associated with lung inflammation. Treatment of SARS-CoV-2-infected K18-hACE2 mice with the AnxA1-mimetic peptide, Ac2-26, reduced lung damage and lethality, without altering the host ability to deal with viral replication. Notably, Ac2-26-treated mice exhibited similar levels of protection to that afforded by the nucleotide analogue Remdesivir, following SARS-CoV-2 infection. Our findings highlight the protective role of the endogenous AnxA1 in mitigating coronavirus-induced lung inflammation and underscore the therapeutic potential of AnxA1 mimetic Ac2-26 as a host-targeted therapy against SARS-CoV-2.

immunology↗

bioRxiv2025

A typology of Australian terrestrial bird communities

AimIncreasing interest in holistic measurement of the response of fauna communities to interventions requires suitable community condition metrics. However, the development of such metrics is hindered by the absence of broad-scale typologies at suitable spatial and ecological resolutions. We aimed to derive a preliminary typology of terrestrial bird communities for Australia, based on bird co-occurrence data, and describe and map the likely distribution of each community type across the continent. LocationMainland Australia, continental islands Time period1973-2022 Major taxa studiedAves MethodsWe used fine-scale co-occurrence data from standard 2-ha surveys in BirdLife Australias citizen-science database. After filtering to reduce bias, we used hierarchical clustering followed by iterative consultation with experts to identify reliably distinct and recognisable terrestrial bird communities across Australia. We used Maxent to model the likely distributions of each community, and developed community descriptions based on each communitys composition and distribution. ResultsThe resultant typology included 29 reliably distinct and recognisable bird communities with major clusters corresponding with seven broad geographical regions. The distributions of bird communities did not correspond tightly to the boundaries of major vegetation groups, with most communities occurring across multiple vegetation types. Main ConclusionsOur preliminary typology of bird communities provides a standard classification at a continental scale. It newly defines distinct bird communities as entities for which condition benchmarks can be established to allow assessment of their conservation status and monitoring of change over time. Refinement will enable cryptic communities in areas with sparse data to be identified. The method could be translated to other regions where adequate coverage of data in the form of standardised surveys of fauna are available. Vast biodiversity datasets delivered through citizen science programs provide the opportunity to develop such typologies for fauna communities, as a precursor to developing targeted and informative community condition metrics.

ecology↗

bioRxiv2024

Acoustic Recognition of Individual Animals in thePresence of Unknown Individuals

Passive acoustic monitoring is firmly established as an effective non-invasive technique for wildlife monitoring. The analysis of animal vocalizations recorded in their natural habitats is commonly used to monitor species occupancy, distribution mapping and community composition. However, the ability to distinguish between individual animals by their vocalisations remains under-explored and presents an exciting opportunity to study individual animal behavior and population demographics in more detail. In this work, we investigate bioacoustic individual-level recognition. In contrast to existing work, we focus on settings where only a subset of the existing population is known and labeled. This is crucial because wildlife populations are constantly changing so that solutions operating only within a known set of individuals are not realistically applicable in the wild. Using two novel datasets, we show that models initially trained to classify only known individuals can also be extended to detect new and previously unknown individuals not included in the training set. We demonstrate that feature extractors pretrained on species classification can be successfully adapted for this task. Extending individual-level recognition to unknown individuals, so-called out-of-distribution classification, is a crucial step towards making individual recognition a realistic possibility in the wild. HighlightsO_LIWe show that features learned by models pretrained on bird species data can be transferred to individual classification tasks with minimal effort. C_LIO_LIWe define and explore the out-of-distribution classification problem on individual animal vocalisations and address various subtleties and eco-logical use cases. C_LIO_LIWe compile and contribute two additional datasets to facilitate further research on individual acoustic recognition. C_LI

bioinformatics↗

bioRxiv2021

Gut microbiota diversity and C-Reactive Protein are predictors of disease severity in COVID-19 patients

Risk factors for COVID-19 disease severity are still poorly understood. Considering the pivotal role of gut microbiota on host immune and inflammatory functions, we investigated the association between changes in gut microbiota composition and the clinical severity of COVID-19. We conducted a multicentre cross-sectional study prospectively enrolling 115 COVID-19 patients categorized according to: 1) WHO Clinical Progression Scale - mild 19 (16.5%), moderate 37 (32.2%) or severe 59 (51.3%); and 2) location of recovery from COVID-19 - ambulatory 14 (household isolation; 12.2%), hospitalized in ward 40 (34.8%) or intensive care unit 61 (53.0%). Gut microbiota analysis was performed through 16S rRNA gene sequencing and data obtained was further related with clinical parameters of COVID-19 patients. Risk factors for COVID-19 severity were identified by univariate and multivariable logistic regression models. In comparison with mild COVID-19 patients, the gut microbiota of moderate and severe patients has: a) lower Firmicutes/Bacteroidetes ratio, b) higher abundance of Proteobacteria; and c) lower abundance of beneficial butyrate-producing bacteria such as Roseburia and Lachnospira genera. Multivariable regression analysis showed that Shannon index diversity (odds ratio [OR] 2.85 [95% CI 1.09-7.41]; p=0.032) and C-Reactive Protein (OR 3.45 [95% CI 1.33-8.91]; p=0.011) were risk factors for COVID-19 severe disease (a score of 6 or higher in WHO clinical progression scale). In conclusion, our results demonstrated that hospitalised moderate and severe COVID-19 patients have microbial signatures of gut dysbiosis and for the first time, the gut microbiota diversity is pointed out as a prognostic biomarker for COVID-19 disease severity.

microbiology↗

bioRxiv2020

Species traits predict extinction risk across the Tree of Life

SummaryBiodiversity is eroding at unprecedented rates due to human activity1. Species’ trajectories towards extinction are shaped by multiple factors, including life-history traits2 as well as human pressures3. Previous studies linking these factors to extinction risk have been narrow in their taxonomic and geographic scope4, thus limiting the ability for identifying global predictors. We studied the relation between 12 traits and the extinction risk of almost 900 species representing 15 groups across the tree of life (vertebrates, invertebrates and plants) at a global scale. We show that threatened species share narrow habitat breadth, poor dispersal ability, low fecundity, small altitudinal range, and are affected by a large human footprint. Other traits either show contrasting responses among groups (body size, offspring size, and change in human footprint), or relations were found for only a limited number of taxa (generation length, diet breadth, microhabitat). Our study suggests that in the absence of data on the precise distribution and population trends of species, traits can be used as predictors of extinction risk and thus help guide future research, monitoring and conservation efforts.Competing Interest StatementThe authors have declared no competing interest.View Full Text

ecology↗

bioRxiv2019

The ELIXIR Core Data Resources: fundamental infrastructure for the life sciences

MotivationLife science research in academia, industry, agriculture, and the health sector depends critically on free and open data resources. ELIXIR (www.elixir-europe.org), the European Research Infrastructure for life sciences data, has identified a set of Core Data Resources within Europe that are of most fundamental importance for the long-term preservation of biological data. We explore characteristics of their usage, impact and assured funding horizon to assess their value and importance as an infrastructure, to understand sustainability of the infrastructure, and to demonstrate a model for assessing Core Data Resources worldwide. ResultsThe nineteen resources currently designated ELIXIR Core Data Resources form a data infrastructure in Europe which is a subset of the worldwide open life science data infrastructure. We show that, from 2014 to 2018, data managed by the Core Data Resources more than tripled while staff numbers increased by less than a tenth. Additionally, support for the Core Data Resources is precarious: together they have assured funding for less than a third of current staff after four years. Our findings demonstrate the importance of the ELIXIR Core Data Resources as repositories for research data and knowledge, while also demonstrating the uncertain nature of the funding environment for this infrastructure. ELIXIR is working towards longer-term support for the Core Data Resources and, through the Global Biodata Coalition, aims to ensure support for the worldwide life science data resource infrastructure of which the ELIXIR Core Data Resources are a subset. Contactrachel.drysdale@elixir-europe.org Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗