Xavier Soberón

Methicillin-resistant (MRSA) and methicillin-susceptible (MSSA) Staphylococcus aureus are major causes of hospital-acquired infections worldwide. However, their genomic features remain underexplored in many regions, particularly in low- and middle-income countries (LMICs). Here, we investigated the genomic diversity, antibiotic resistance, and virulence traits of methicillin-resistant (MRSA) and methicillin-susceptible (MSSA) Staphylococcus aureus isolates from three tertiary care hospitals in Mexico City. A total of 101 isolates collected between 2006 and 2019 from newborns and adults with diverse infections were analyzed using whole-genome sequencing. MRSA isolates were restricted to clonal complexes CC5 and CC8, whereas MSSA strains displayed a broader diversity across multiple lineages. A distinct clade of CC8-MRSA isolates identified in 2013 among newborns was closely related to the USA300 lineage but carried SCC mec IVc without the Panton-Valentine leukocidin genes and the COMER island. Similarly, a localized cluster of CC5-MSSA isolates from neonates in 2012 showed genomic variations largely driven by prophage-associated elements. MRSA strains carried a higher burden of resistance genes, including fluoroquinolone-associated mutations, whereas MSSA isolates exhibited greater heterogeneity in virulence genes and spa types. Both groups shared a conserved virulence gene repertoire; however, variations in the virulence genes highlighted lineage-specific pathogenic features. IMPORTANCE: MRSA and MSSA S. aureus genomes are still largely unstudied in Mexico although they are frequently found in hospitals. This study provides a long-term genomic analysis of MRSA and MSSA isolates from three hospitals in Mexico. Our findings revealed the presence of S. aureus international clones of clonal complexes CC5 and CC8 over a decade, broader diversity in MSSA, and localized clonal transmission within hospitals. The contrasting resistance and virulence profiles of MRSA and MSSA clones underscore the need for genomic surveillance frameworks to inform infection control and antibiotic stewardship in healthcare settings.

The COVID-19 pandemic, caused by SARS-CoV-2, has led to significant challenges worldwide, including diverse clinical outcomes and prolonged post-recovery symptoms known as Long COVID or Post-COVID-19 syndrome. Emerging evidence suggests a crucial role of metabolic reprogramming in the infection’s long-term consequences. This study employs a novel approach utilizing machine learning (ML) and explainable artificial intelligence (XAI) to analyze metabolic alterations in COVID-19 and Post-COVID-19 patients. By integrating ML with SHAP (SHapley Additive exPlanations) values, we aimed to uncover metabolomic signatures and identify potential biomarkers for these conditions. Our analysis included a cohort of 142 COVID-19, 48 Post-COVID-19 samples and 38 CONTROL patients, with 111 identified metabolites. Traditional analysis methods like PCA and PLS-DA were compared with advanced ML techniques to discern metabolic changes. Notably, XGBoost models, enhanced by SHAP for explainability, outperformed traditional methods, demonstrating superior predictive performance and providing different insights into the metabolic basis of the disease’s progression and its aftermath, the analysis revealed several metabolomic subgroups within the COVID-19 and Post-COVID-19 conditions, suggesting heterogeneous metabolic responses to the infection and its long-term impacts. This study highlights the potential of integrating ML and XAI in metabolomics research.

The COVID-19 pandemic negatively affected the progress in accessing essential Tuberculosis (TB) services and reducing the burden of TB disease, resulting in a decreased detection of new cases and increased deaths. Generating molecular diagnostic tests with faster results without losing reliability is considered a priority.

Next-Generation Sequencing (NGS) is widely used to investigate genomic variation. In several studies, the genetic variation ofMycobacterium tuberculosishas been analyzed in sputum samples without previous culture, using target enrichment methodologies for NGS. Alignments obtained by different programs generally map the sequences under default parameters, and from these results, it is assumed that onlyMycobacteriumreads will be obtained. However, variants of interest microorganism in clinical samples can be confused with a vast collection of reads from other bacteria, viruses, and human DNA. Currently, there are no standardized pipelines, and the cleaning success is never verified since there is a lack of rigorous controls to identify and remove reads from other sputum-microorganisms genetically similar toM.tuberculosis. Therefore, we designed a bioinformatic pipeline to process NGS data from sputum samples, including several filters and quality control points to identify and eliminate non-M.tuberculosisreads to obtain a reliable genetic variant report. Our proposal uses the SURPI software as a taxonomic classifier to filter input sequences and perform a mapping that provides the highest percentage ofMycobacteriumreads, minimizing the reads from other microorganisms. We then use the filtered sequences to perform variant calling with the GATK software, ensuring the mapping quality, realignment, recalibration, hard-filtering, and post-filter to increase the reliability of the reported variants. Using default mapping parameters, we identified reads of contaminant bacteria, such asStreptococcus,Rhotia,Actinomyces, andVeillonella. Our final mapping strategy allowed a sequence identity of 97.8% between the input reads and the wholeM.tuberculosisreference genomeH37Rvusing a genomic edit distance of three, thus removing 98.8% of the off-target sequences with aMycobacteriumreads loss of 1.7%. Finally, more than 200 unreliable genetic variants were removed during the variant calling, increasing the report’s reliability.

Mycobacterium tuberculosis infection has three discernible outcomes: active tuberculosis, latent tuberculosis, or clearance of the bacterium. The outcome of the infection depends on the interaction of the bacterium, the immune system, and the microbiome of the host. The current study uses 16S rRNA sequencing to determine the diversity and composition of the respiratory microbiome of drug-resistant and drug-sensitive tuberculosis patients as well as healthy volunteers. Tuberculosis patients exhibited increased microbial diversity and differentially abundant bacteria than healthy volunteers. Compositional differences were also observed when comparing drug-sensitive or -resistant tuberculosis patients. Finally, we defined and assessed the differences in the core sputum microbiota between tuberculosis patients and healthy volunteers. Our observations collectively suggest that in sputum, Mycobacterium tuberculosis infection is related to altered bacterial diversity and compositional differences of core members of the microbiome, with potential implications for the bacterial pulmonary ecosystem’s stability and function.

The hypothalamus-pituitary-thyroid (HPT) axis regulates energy balance through the pleiotropic action of thyroid hormones. HPT basal activity and stimulation by cold or voluntary exercise are repressed by previous chronic stress in adults. Maternal separation (MS) modifies HPT basal activity; we thus studied the response of the axis to energy demands and analyzed possible epigenetic changes on Trh promoter. Nonhandled (NH) or MS male Wistar rats were cold exposed 1 h at adulthood; Trh expression in the hypothalamic paraventricular nucleus (PVN) and serum thyrotropin (TSH) concentration were increased only in NH rats. Two weeks of voluntary exercise decreased fat mass and increased Trh expression, and thyroid hormones concentration changed proportionally to running distance in NH male rats and MS male rats. Although NH females ran more than MS and much more than males, exercise decreased body weight and fat mass only in NH rats with no change on any parameter of the HPT axis but increased Pomc expression in arcuate-nucleus of NH and Npy in MS females. Overall, the methylation pattern of PVN Trh gene promoter was similar in NH males and females; MS modified methylation of specific CpG sites, a thyroid hormone receptor (THR)-binding site present after the initiation site was hypomethylated in MS males; in MS females, the THR binding site of the proximal promoter (site 4) and 2 sites in the first intron were hypermethylated. Our studies showed that, in a sex-dimorphic manner, MS blunted the responses of HPT axis to energy demands in adult animals and caused methylation changes on Trh promoter that could alter T3 feedback.

Staphylococcus epidermidis is a human commensal and pathogen worldwide distributed. In this work, we surveyed for multi-resistant S. epidermidis strains in eight years at a children health-care unit in México City. Multidrug-resistant S. epidermidis were present in all years of the study. Resistance to methicillin, beta-lactams, fluoroquinolones, and macrolides were included. To understand the genetic basis of antibiotic resistance and its association with virulence and gene exchange, we sequenced the genomes of 17 S. epidermidis isolates. Whole-genome nucleotide identities between all the pairs of S. epidermidis strains were about 97% to 99%. We inferred a clonal structure and eight Multilocus Sequence Types (MLST´s) in the S. epidermidis sequenced collection. The profile of virulence includes genes involved in biofilm formation and phenol-soluble modulins (PSMs). However, half of the S. epidermidis analyzed lacked the icaoperon for biofilm formation. Likely, they are commensal S. epidermidis strains but multi-antibiotic resistant. Uneven distribution of insertion sequences, phages, and CRISPR-Cas immunity phage systems suggest frequent horizontal gene transfer. Rates of recombination between S. epidermidis strains were more prevalent than the mutation rate and affected the whole genome. Therefore, the multidrug-resistance, independently of the pathogenic traits, might explain the persistence of specific highly adapted S. epidermidis clonal lineages in nosocomial settings.

Staphylococcus epidermidis is a human commensal and pathogen worldwide distributed. In this work, we surveyed for multi-resistant S. epidermidis strains in eight years at a children health-care unit in México City. Multidrug-resistant S. epidermidis were present in all years of the study. Resistance to methicillin, beta-lactams, fluoroquinolones, and macrolides were included. To understand the genetic basis of antibiotic resistance and its association with virulence and gene exchange, we sequenced the genomes of 17 S. epidermidis isolates. Whole-genome nucleotide identities between all the pairs of S. epidermidis strains were about 97% to 99%. We inferred a clonal structure and eight Multilocus Sequence Types (MLST´s) in the S. epidermidis sequenced collection. The profile of virulence includes genes involved in biofilm formation and phenol-soluble modulins (PSMs). However, half of the S. epidermidis analyzed lacked the icaoperon for biofilm formation. Likely, they are commensal S. epidermidis strains but multi-antibiotic resistant. Uneven distribution of insertion sequences, phages, and CRISPR-Cas immunity phage systems suggest frequent horizontal gene transfer. Rates of recombination between S. epidermidis strains were more prevalent than the mutation rate and affected the whole genome. Therefore, the multidrug-resistance, independently of the pathogenic traits, might explain the persistence of specific highly adapted S. epidermidis clonal lineages in nosocomial settings.