The presence of Salmonella in rivers, lakes, or beaches in South America represents a challenge to public health and aquatic ecosystems. This review explores the distribution, prevalence, and the main factors contributing to the survival and spread of Salmonella, including wastewater discharge, agricultural runoff, and climatic variables such as high temperatures and precipitation. These factors also facilitate the distribution of multidrug-resistant strains in water. The review is based on bibliographic searches in various databases, focusing on Salmonella species, South American countries, and types of water bodies. Predominant serovars include S. Enteritidis and S. Typhimurium, with S. Typhi and S. Panama frequently detected in Chile, S. Enteritidis in Argentina, and S. Typhimurium in Brazil. Less common serovars, including S. Dublin and S. Paratyphi B, were identified, along with subspecies such as diarizonae and houtenae. These findings highlight the role of environmental, physicochemical, and anthropogenic factors influencing Salmonella dynamics. The review identifies research gaps, advocating for further studies to better understand the interactions between Salmonella, climate change, and human activity. Strengthening surveillance and mitigation strategies is crucial to protect water resources and public health in South America.

Moraxella catarrhalis is an opportunistic pathogen of the human respiratory tract, primarily associated with otitis media in children and exacerbations of chronic obstructive pulmonary disease in adults. Despite its clinical importance, the genomic diversity and functional specialization of M. catarrhalis remain insufficiently characterized. This study aimed to analyse the global genetic diversity of M. catarrhalis using whole-genome sequencing to identify phylogenetic lineages, antimicrobial resistance patterns and key virulence factors. Phylogenomic analysis of 345 publicly available genomes identified 3 phylogroups, of which 1 exhibited significant genomic divergence and was excluded from further analyses due to its potential classification as a separate species. The remaining two phylogroups corresponded to previously described seroresistant and serosensitive lineages. Phylogroup B exhibited a higher prevalence of antimicrobial resistance genes, particularly bro-1 and bro-2, while phylogroup A exhibited unique metabolic adaptation, including genes encoding for the DppB-DppC-DppD dipeptide transport system. Both phylogroups shared crucial virulence factors, including UspA1 and UspA2, which facilitate adhesion and immune evasion. Potential therapeutic targets were identified, including PilQ, essential for type IV pilus biogenesis, and CopB, which plays a key role in iron acquisition and immune evasion. Overall, these findings highlight the significance of phylogenomics approaches in elucidating the genetic mechanisms underlying pathogenicity and resistance in M. catarrhalis, providing insights for future therapeutic and preventive strategies.

Kiwifruit (Actinidia deliciosa [A. Chev.], C.V. Liang & A. R. Ferguson, 1984) is a perennial plant, with morphologically hermaphroditic and functionally dioecious flowers. Fruits of this species are berries of great commercial and nutritional importance. Nevertheless, few studies have analyzed the molecular mechanisms involved in sexual differentiation in this species. To determine these mechanisms, we performed RNA-seq in floral tissue at stage 60 on the BBCH scale in cultivar ‘Hayward’ (H, female) and a seedling from ‘Green Light’ × ‘Tomuri’ (G × T, male). From these analyses, we obtained expression profiles of 24,888 (H) and 27,027 (G × T) genes, of which 6413 showed differential transcript abundance. Genetic ontology (GO) and KEGG analysis revealed activation of pathways associated with the translation of hormonal signals, plant-pathogen interaction, metabolism of hormones, sugars, and nucleotides. The analysis of the protein-protein interaction network showed that the genes ERL1, AG, AGL8, LFY, WUS, AP2, WRKY, and CO, are crucial elements in the regulation of the hormonal response for the formation and development of anatomical reproductive structures and gametophytes. On the other hand, genes encoding four Putative S-adenosyl-L-methionine-dependent methyltransferases (Achn201401, Achn281971, Achn047771 and Achn231981) were identified, which were up-regulated mainly in the male flowers. Moreover, the expression profiles of 15 selected genes through RT-qPCR were consistent with the results of RNA-seq. Finally, this work provides gene expression-based interactions between transcription factors and effector genes from hormonal signaling pathways, development of floral organs, biological and metabolic processes or even epigenetic mechanisms which could be involved in the kiwi sex-determination. Thus, in order to decode the nature of these interactions, it could be helpful to propose new models of flower development and sex determination in the Actinidia genus.

Waterborne illnesses, including those caused by Salmonella, are an increasing public health challenge, particularly in developing countries. Potential sources of salmonellosis include fruits and vegetables irrigated/treated with surface water, leading to human infections. Salmonella causes millions of gastroenteritis cases annually, but early detection through routine water quality surveillance is time-consuming, requires specialized equipment, and faces limitations, such as coverage gaps, delayed data, and poor accessibility. Climate change-driven extreme events such as floods and droughts further exacerbate variability in water quality. In this context, remote sensing offers an efficient and cost-effective alternative for environmental monitoring. This study evaluated the potential of Sentinel-2 satellite imagery to predict Salmonella occurrence in the Maipo and Mapocho river basins (Chile) by integrating spectral, microbiological, climatic, and land use variables. A total of 1851 water samples collected between 2019 and 2023, including 704 positive samples for Salmonella, were used to develop a predictive model. Predicting Salmonella in surface waters using remote sensing is challenging for several reasons. Satellite sensors capture environmental proxies (e.g., vegetation cover, surface moisture, and turbidity) but not pathogens. Our goal was to identify proxies that reliably correlate with Salmonella. Twelve spectral indices (e.g., NDVI, NDWI, and MNDWI) were used as predictors to develop a predictive model for the presence of the pathogen, which achieved 59.2% accuracy. By spatially interpolating the occurrences, it was possible to identify areas with the greatest potential for Salmonella presence. NDWI and AWEI were most strongly correlated with Salmonella presence in high-humidity areas, and spatial interpolation identified the higher-risk zones. These findings reveal the challenges of using remote sensing to identify environmental conditions conducive to the presence of pathogens in surface waters. This study highlights the methodological challenges that must be addressed to make satellite-based surveillance an accessible and effective public health tool. By integrating satellite data with environmental and microbiological analyses, this approach can potentially strengthen low-cost, proactive environmental monitoring for public health decision-making in the context of climate change.