Biology subjects

Carvalho, B.

Publications and source records attributed to Carvalho, B..

4 recordsLinked to original sources

bioRxiv2026

Integrated Resistome and Quantitative Proteomics Reveal Coordinated Resistance Architecture in MDR and XDR Gram-Negative ICU Pathogens

ObjectivesAntimicrobial resistance (AMR) in Gram-negative pathogens is driven by complex and coordinated molecular mechanisms that remain incompletely characterized. This study integrated phenotypic, genomic, and quantitative proteomic analyses to characterize multidrug-resistant (MDR) and extensively drug-resistant (XDR) Gram-negative bacteria circulating in an intensive care unit (ICU) in Northeastern Brazil. MethodsA total of 259 Gram-negative isolates collected between 2019 and 2021 underwent species identification, antimicrobial susceptibility testing, and targeted qPCR for resistance genes. Klebsiella pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa representing susceptible, MDR, and XDR phenotypes were selected for whole-genome sequencing and label-free quantitative proteomics. Differential protein abundance was assessed using Limma with |log2FC| > 1 and p < 0.05. ResultsK. pneumoniae (47%), A. baumannii (24%), and P. aeruginosa (21%) predominated. Carbapenem resistance reached 44%, 93%, and 61%, respectively, and MDR/XDR phenotypes occurred in >30% of isolates. Genomic analyses revealed dense resistomes with coexisting {beta}-lactamases (blaKPC, blaNDM, blaCTX-M, OXA) and widespread efflux systems. Proteomic profiling demonstrated phenotype-associated differences in outer membrane proteins, transport systems, regulatory proteins, and metabolic pathways. XDR isolates showed additional enrichment of envelope remodeling proteins, stress response mechanisms, and proteostasis-associated factors. ConclusionsMDR and XDR Gram-negative ICU pathogens exhibit coordinated resistance architecture characterized by accumulation of resistance genes and adaptive proteomic remodeling. Integrated multi-omics approaches provide mechanistic insight into antimicrobial resistance and support improved surveillance and therapeutic strategies. What is known?O_LIAntimicrobial resistance is a priority and a serious problem in global health, resulting in high rates of morbidity and mortality. C_LIO_LIKlebsiella pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa are on the World Health Organizations (WHO) priority list as major causes of morbidity and mortality worldwide. C_LIO_LIClassical characterization of susceptibility and resistance phenotypes does not capture the complexity of antimicrobial resistance and hampers effective control measures and actions to minimize the evolutionary dynamics of resistance in these bacteria. C_LI What is new?O_LIThe study characterizes the phenotypic pattern of antimicrobial susceptibility, the presence and sequencing of the resistome and virulome, and analyzes the label-free quantitative proteome of susceptible, MDR, and XDR phenotypes in strains of K. pneumoniae, A. baumannii, and P. aeruginosa circulating in hospital ICUs in Brazil. C_LIO_LIMDR and XDR gram-negative phenotypes are associated with a dense resistome, with widespread dissemination of beta-lactamase genes (bla_KPC, bla_NDM, bla_CTX-M, and OXA) and RND-type (MEXs) and acrAB-tolC efflux pumps, without changes in virulence genes. C_LIO_LIProteomic analysis demonstrated increased production of beta-lactamases, components of efflux pump systems, outer membrane protein synthesis, protection for oxidative stress mechanisms, proteins for iron acquisition, and systemic regulators. XDR strains additionally showed enhanced remodeling of the cell envelope, activation of proteostasis, and metabolic adaptation. C_LI

microbiology↗

bioRxiv2026

Mitotic errors drive rapid clearance of polyploidy during intestinal regeneration despite robust centrosome clustering

Polyploid cells are increasingly recognized not only as hallmarks of cancer but also as features of regenerating tissues. During intestinal regeneration, polyploid cells are transient, yet the mechanisms underlying their clearance remain unknown. Using mouse intestinal organoids as a regeneration model, we show that, unlike in many cancer cell-line models, this clearance occurs without immediate cell-cycle arrest and is not driven by failure to establish spindle bipolarity. Instead, polyploid intestinal cells efficiently cluster supernumerary centrosomes to form bipolar spindles in an HSET-dependent manner, facilitated by delayed centrosome separation at mitotic onset. Despite this, polyploid divisions frequently produce chromosome segregation errors, including catastrophic chronocrisis. Lineage tracing reveals that progeny of such divisions is rapidly lost over subsequent generations. Increasing polyploidy during early regeneration disrupts organoid maturation, indicating that timely polyploidy clearance is required for successful regeneration. Polyploid cells are also detected in regenerating human colonic organoids, suggesting that transient polyploidy is a conserved feature of intestinal regeneration.

cell biology↗

bioRxiv2024

Karyotype Evolution in Response to Chemoradiotherapy and Upon Recurrence of Esophageal Adenocarcinomas.

The genome of esophageal adenocarcinoma (EAC) is highly unstable and might evolve over time. Here, we track karyotype evolution in EACs in response to treatment and upon recurrence through multi-region and longitudinal analysis. To this end, we introduce L-PAC, a bio-informatics technique that allows inference of absolute copy number aberrations (CNA) of low-purity samples by leveraging information of high-purity samples from the same cancer. Quantitative analysis of matched absolute CNAs reveals that the amount of karyotype evolution induced by chemoradiotherapy (CRT) is predictive for early recurrence and depends on the initial level of karyotype intra-tumor heterogeneity. We observe that CNAs acquired in response to CRT are partially reversed back to the initial state upon recurrence. CRT hence alters the fitness landscape to which tumors can adjust by adapting their karyotype. Together, our results indicate that karyotype plasticity contributes to therapy resistance of EACs.

bioinformatics↗

bioRxiv2022

Data-Driven Predictions of Potential Leishmania Vectors in Latin America

The incidence of vector-borne diseases is rising as deforestation, climate change, and globalization bring humans in contact with arthropods that can transmit pathogens. In particular, incidence of American Cutaneous Leishmaniasis (ACL), a parasitic disease transmitted by sandflies, is increasing as previously intact habitats are cleared for agriculture and urban areas, potentially bringing people into contact with vectors and reservoir hosts. Previous evidence has identified dozens of sandfly species that have been infected with and/or transmit Leishmania parasites. However, there is an incomplete understanding of which sandfly species transmit the parasite, complicating efforts to limit disease spread. Here, we apply machine learning models (boosted regression trees) to leverage biological and geographical traits of known sandfly vectors to predict potential vectors. Additionally, we generate trait profiles of confirmed vectors and identify important factors in transmission. Our model performed well with an average out of sample accuracy of 86%. The models predict that synanthropic sandflies living in areas with greater canopy height, less human modification, and within an optimal range of rainfall are more likely to be Leishmania vectors. We also observed that generalist sandflies that are able to inhabit many different ecoregions are more likely to transmit the parasite. Our results suggest that Psychodopygus amazonensis and Nyssomia antunesi are unidentified potential vectors, and should be the focus of sampling and research efforts. Overall, we found that our machine learning approach provides valuable information for Leishmania surveillance and management in an otherwise complex and data sparse system. Author SummaryAmerican Cutaneous Leishmaniasis (ACL) is a neglected parasitic disease transmitted by sandflies in Latin America. There is an incomplete understanding of which sandfly species transmit the parasite, complicating efforts to limit disease spread. In this study, the authors created a database of sandfly traits, then used predictive models to determine important factors in disease transmission and how different climate and environmental variables affect ACL transmission. The models suggest that transmission occurs at the interface between domestic habitats and well-preserved forests. The authors also generate predictions of which sandflies might be transmitting the parasite that are not known vectors at the time, specifically Psychodopygus amazonensis and Nyssomia antunesi. This new knowledge can lead to a better understanding of the system of transmission, and can point to possible hotspots of the disease. The analysis can also help direct researchers to areas of interest for sampling studies, as well as specific sandflies to focus their effort on.

ecology↗