Biology subjects

Matta, J.

Publications and source records attributed to Matta, J..

5 recordsLinked to original sources

bioRxiv2026

Expanding Threat of Carbapenemase-Producing Escherichia coli and Klebsiella pneumoniae in Peru: Genomic and Phenotypic Evidence of High-Risk Clones Dissemination

Carbapenemase-producing Enterobacterales represent a growing global threat due to their extensive antimicrobial resistance and rapid dissemination. This study characterized the phenotypic and genomic features of Escherichia coli and Klebsiella pneumoniae isolates collected between 2020 and 2022 from four healthcare institutions in Lima, Peru. A total of 320 non-redundant isolates (61 E. coli and 259 K. pneumoniae) were analyzed through antimicrobial susceptibility testing, polymerase chain reaction, and whole-genome sequencing. The most frequent carbapenemase gene was blaNDM (69%), followed by blaKPC (16.9%) and blaOXA-48-like (4.6%). Eleven K. pneumoniae isolates co-produced NDM and KPC, and one E. coli isolate co-harbored NDM and OXA-48-like. All isolates were multidrug resistant, and 5% were pandrug resistant. Novel {beta}-lactam/{beta}-lactamase inhibitor combinations such as aztreonam/avibactam and cefiderocol showed complete activity against all classes of carbapenemases. Genomic analysis revealed predominant E. coli sequence types ST167 and ST410 and K. pneumoniae lineages ST147, ST15, ST45, and ST273. The blaNDM-5 allele was detected for the first time in Peru, mostly in E. coli ST167, carried on multireplicon IncF-type plasmids. In K. pneumoniae, ST147 was identified as a dominant clone associated with blaNDM-1, indicating sustained local dissemination of high-risk clonal groups. The coexistence of multiple carbapenemases and plasmid backbones highlights the ongoing evolution of resistance mechanisms. These findings provide actionable evidence to guide treatment strategies in settings with high prevalence of metallo-{beta}-lactamases and underscores the need for continuous genomic surveillance and antimicrobial stewardship to mitigate their clinical and epidemiological impact.

microbiology↗

bioRxiv2024

The Gut Microbiome Controls Liver Tumors via the Vagus Nerve

Liver cancer ranks amongst the deadliest cancers. Nerves have emerged as an understudied regulator of tumor progression. The parasympathetic vagus nerve influences systemic immunity via acetylcholine (ACh). Whether cholinergic neuroimmune interactions influence hepatocellular carcinoma (HCC) remains uncertain. Liver denervation via hepatic vagotomy (HV) significantly reduced liver tumor burden, while pharmacological enhancement of parasympathetic tone promoted tumor growth. Cholinergic disruption in Rag1KO mice revealed that cholinergic regulation requires adaptive immunity. Further scRNA-seq and in vitro studies indicated that vagal ACh dampens CD8+ T cell activity via muscarinic ACh receptor (AChR) CHRM3. Depletion of CD8+ T cells abrogated HV outcomes and selective deletion of Chrm3 on CD8+ T cells inhibited liver tumor growth. Beyond tumor-specific outcomes, vagotomy improved cancer-associated fatigue and anxiety-like behavior. As microbiota transplantation from HCC donors was sufficient to impair behavior, we investigated putative microbiota-neuroimmune crosstalk. Tumor, rather than vagotomy, robustly altered fecal bacterial composition, increasing Desulfovibrionales and Clostridial taxa. Strikingly, in tumor-free mice, vagotomy permitted HCC-associated microbiota to activate hepatic CD8+ T cells. These findings reveal that gut bacteria influence behavior and liver anti-tumor immunity via a dynamic and pharmaceutically targetable, vagus-liver axis.

cancer biology↗

bioRxiv2023

CCT and Cullin1 regulate the TORC1 pathway to promote dendritic arborization in health and disease.

The development of cell-type-specific dendritic arbors is integral to the proper functioning of neurons within their circuit networks. In this study, we examine the regulatory relationship between the cytosolic chaperonin CCT, key insulin pathway genes, and an E3 ubiquitin ligase (Cullin1) in homeostatic dendritic development. CCT loss of function (LOF) results in dendritic hypotrophy in Drosophila Class IV (CIV) multidendritic larval sensory neurons, and CCT has recently been shown to fold components of the TOR (Target of Rapamycin) complex 1 (TORC1), in vitro. Through targeted genetic manipulations, we have confirmed that LOF of CCT and the TORC1 pathway reduces dendritic complexity, while overexpression of key TORC1 pathway genes increases dendritic complexity in CIV neurons. Both CCT and TORC1 LOF significantly reduce microtubule (MT) stability. CCT has been previously implicated in regulating proteinopathic aggregation, thus we examined CIV dendritic development in disease conditions as well. Expression of mutant Huntingtin leads to dendritic hypotrophy in a repeat-length-dependent manner, which can be rescued by TORC1 disinhibition via Cullin1 LOF. Together, our data suggest that Cullin1 and CCT influence dendritic arborization through regulation of TORC1 in both health and disease. SIGNIFICANCEThe insulin pathway has become an increasingly attractive target for researchers interested in understanding the intersection of metabolism and brain health. We have found connections between the insulin pathway and cytosolic protein maintenance in the development of neuronal dendrites. These pathways converge on the dendritic cytoskeleton, particularly microtubules. Neurons expressing mutant Huntingtin also show defects in dendritic development and the underlying cytoskeleton, and we find that disinhibition of the insulin pathway can rescue dendritic hypotrophy in these neurons. This work advances our understanding of the molecular interactions between the insulin pathway and neuronal development in both health and Huntingtons Disease conditions.

neuroscience↗

bioRxiv2021

Characterization and tissue localization of zebrafish homologs of the human ABCB1 multidrug transporter

Given its similarities with mammalian systems, the zebrafish has emerged as a potential model to study the blood-brain barrier (BBB). Capillary endothelial cells at the human BBB express high levels of P-glycoprotein (P-gp, encoded by the ABCB1 gene) and ABCG2 (encoded by the ABCG2 gene). However, little information has been available about ATP-binding cassette transporters expressed at the zebrafish BBB. In this study, we focus on the characterization and tissue localization of two genes that are similar to human ABCB1, zebrafish abcb4 and abcb5. Cytotoxicity assays with stably-transfected cell lines revealed that zebrafish Abcb5 cannot efficiently transport the substrates doxorubicin and mitoxantrone compared to human P-gp and zebrafish Abcb4. Additionally, zebrafish Abcb5 did not transport the fluorescent probes BODIPY-ethylenediamine or LDS 751, while they were readily transported by Abcb4 and P-gp. A high-throughput screen conducted with 90 human P-gp substrates confirmed that zebrafish Abcb4 has overlapping substrate specificity with P-gp. Basal ATPase activity of zebrafish Abcb4 and Abcb5 was comparable to that of human P-gp. In the brain vasculature, RNAscope probes to detect abcb4 colocalized with staining by the P-gp antibody C219, while abcb5 was not detected. Zebrafish abcb4 also colocalized with claudin-5 expression in brain endothelial cells. Abcb4 and Abcb5 had different tissue localizations in multiple zebrafish tissues, consistent with different functions. The data suggest that zebrafish Abcb4 most closely phenocopies P-gp and that the zebrafish may be a viable model to study the role of the multidrug transporter P-gp at the BBB.

pharmacology and toxicology↗

bioRxiv2019

Biomarker discovery in inflammatory bowel diseases using network-based feature selection

Reliable identification of inflammatory biomarkers from metagenomics data is a promising direction for developing non-invasive, cost-effective, and rapid clinical tests for early diagnosis of IBD. We present an integrative approach to Network-Based Biomarker Discovery (NBBD) which integrates network analyses methods for prioritizing potential biomarkers and machine learning techniques for assessing the discriminative power of the prioritized biomarkers. Using a large dataset of new-onset pediatric IBD metagenomics biopsy samples, we compare the performance of Random Forest (RF) classifiers trained on features selected using a representative set of traditional feature selection methods against NBBD framework, configured using five different tools for inferring networks from metagenomics data, and nine different methods for prioritizing biomarkers as well as a hybrid approach combining best traditional and NBBD based feature selection. We also examine how the performance of the predictive models for IBD diagnosis varies as a function of the size of the data used for biomarker identification. Our results show that (i) NBBD is competitive with some of the state-of-the-art feature selection methods including Random Forest Feature Importance (RFFI) scores; and (ii) NBBD is especially effective in reliably identifying IBD biomarkers when the number of data samples available for biomarker discovery is small.

bioinformatics↗