Biology subjects

Salazar, V. W.

Publications and source records attributed to Salazar, V. W..

6 recordsLinked to original sources

bioRxiv2025

Chemosynthesis enhances carbon fixation in an active microbialite ecosystem

Microbialites--carbonate structures formed under the influence of microbial action-- are the earliest macroscopic evidence of life. For three billion years, the microbial mat communities responsible for these structures fundamentally shaped Earths biogeochemical cycles. In photosynthetic microbial communities, light energy ultimately drives primary production and the ensuing cascade of daisy-chained metabolisms. However, reduced compounds such as trace gases and those released as metabolic byproducts in deeper, anoxic regions of the mat, could also fuel chemosynthetic processes. Here, we investigated the intricate metabolic synergies that sustain microbialite community nutrient webs. We recovered 331 genomes spanning 40 bacterial and archaeal phyla, revealing a staggering diversity fuelled by the biogeochemistry of these ecosystems. While phototrophy is an important metabolism encoded by 17% of the genomes, over half encode enzymes to harness energy from reduced compounds and 12% co-encode carbon fixation pathways, using sulfide and hydrogen as major electron donors. Consistent with these genomic predictions, we experimentally demonstrated that microbialite communities oxidise ferrous iron, ammonia, sulfide and gas substrates aerobically and anaerobically. Furthermore, carbon isotopic assays revealed that diverse chemosynthetic pathways contribute significantly to carbon fixation and ecosystem organic matter production alongside photosynthesis. Chemosynthesis in microbialite communities represents a complex interplay of metabolic synergies and continuous nutrient cycling, which decouples community carbon fixation from the diurnal cycle. As a result, this process mitigates the loss of organic carbon from respiration, enhancing the net productivity of these highly efficient ecosystems. SignificanceMicrobialite ecosystems are among the most ancient on Earth, having dominated the biosphere for over three billion years and persisting into the present. They serve as critical models for studying past and present Earth-biosphere interactions. In this study, we challenge the paradigm that photosynthesis is the main driver of microbialite primary productivity, emphasizing the fundamental role of chemosynthesis in the global element cycle both in modern extreme environments and throughout Earths history. Altogether, our findings provide novel insight into these unique microbial ecosystems, which may have functioned as hotspots for metabolic innovation over geological time.

microbiology↗

bioRxiv2024

Global picoplankton biogeography revealed by metagenomic and climatic data integration

Microbial plankton play fundamental roles in biogeochemical cycles, driving nutrient cycling that influences the global climate and supports life on Earth. Picoplankton are the smallest and most abundant planktonic organisms. The distribution and ecology of these organisms is determined by environmental factors and their biogeography is largely shaped by basin-scale patterns of physicochemical composition of ocean waters. The increased availability of high-throughput sequencing data of microbial communities has enabled the description of how the global oceans are partitioned into distinct microbial biogeographical provinces. However, the key attributes associated with such provinces are still unclear. Here we present a model of picoplankton biogeography based on 1454 metagenomes from multiple sampling consortia, resulting in the largest integrated surface ocean metagenome analysis to date. We identify ten distinct groups based on metagenomic dissimilarity, divided into three categories: polar (Arctic and Antarctic), temperate (coastal temperate, temperate/subtropical transition, oceanic temperate, Mediterranean-like) and tropical (tropical low nutrient, tropical high nutrient, subtropical oceanic gyres). Using machine learning and omics data integration techniques, we predict province areas across the surface oceans and describe their environmental, taxonomical, and functional features. We quantify the relationship between environmental factors and each biogeographical province, identify their main representative taxa and the importance of carbon degradation and antimicrobial resistance pathways in functional community composition, and discuss implications for establishing a model for global picoplankton biogeography.

ecology↗

bioRxiv2023

Metaphor - A workflow for streamlined assembly and binning of metagenomes

Recent advances in bioinformatics and high-throughput sequencing have enabled the large-scale recovery of genomes from metagenomes. This has the potential to bring important insights as researchers can bypass cultivation and analyse genomes sourced directly from environmental samples. There are, however, technical challenges associated with this process, most notably the complexity of computational workflows required to process metagenomic data, which include dozens of bioinformatics software tools, each with their own set of customisable parameters that affect the final output of the workflow. At the core of these workflows are the processes of assembly - combining the short input reads into longer, contiguous fragments (contigs), and binning - clustering these contigs into individual genome bins. Both processes can be done for each sample separately or by pooling together multiple samples to leverage information from a combination of samples. Here we present Metaphor, a fully-automated workflow for genome-resolved metagenomics (GRM). Metaphor differs from existing GRM workflows by offering flexible approaches for the assembly and binning of the input data, and by combining multiple binning algorithms with a bin refinement step to achieve high quality genome bins. Moreover, Metaphor generates reports to evaluate the performance of the workflow. We showcase the functionality of Metaphor on different synthetic datasets, and the impact of available assembly and binning strategies on the final results. The workflow is freely available at https://github.com/vinisalazar/metaphor. Author summaryWe present Metaphor, a user-friendly, automated workflow for the recovery of genomes from metagenomes. Our tool offers flexible options for assembling and binning metagenomic contigs, that may be adjusted according to the characteristics of the input data and available computational resources, and a combination of binning algorithms, which improves the quantity and quality of resulting genome bins. We showcase the performance of Metaphor on synthetic benchmarking datasets and discuss the implication of methodological decisions regarding the strategy for assembling and binning metagenomic contigs.

bioinformatics↗

bioRxiv2021

Inhibition of SARS-CoV-2 infection in human cardiomyocytes by targeting the Sigma-1 receptor disrupts cytoskeleton architecture and contractility

Heart dysfunction, represented by conditions such as myocarditis and arrhythmia, has been reported in COVID-19 patients. Therapeutic strategies focused on the cardiovascular system, however, remain scarce. The Sigma-1 receptor (S1R) has been recently proposed as a therapeutic target because its inhibition reduces SARS-CoV-2 replication. To investigate the role of S1R in SARS-CoV-2 infection in the heart, we used human cardiomyocytes derived from induced pluripotent stem cells (hiPSC-CM) as an experimental model. Here we show that the S1R antagonist NE-100 decreases SARS-CoV-2 infection and viral replication in hiPSC-CMs. Also, NE-100 reduces cytokine release and cell death associated with infection. Because S1R is involved in cardiac physiology, we investigated the effects of NE-100 in cardiomyocyte morphology and function. We show that NE-100 compromises cytoskeleton integrity and reduces beating frequency, causing contractile impairment. These results show that targeting S1R to challenge SARS-CoV-2 infection may be a useful therapeutic strategy but its detrimental effects in vivo on cardiac function should not be ignored.

cell biology↗

bioRxiv2020

Insights on the taxonomy and ecogenomics of the Synechococcus collective

The genus Synechococcus (also named Synechococcus collective, SC) is a major contributor to global primary productivity. It is found in a wide range of aquatic ecosystems. Synechococcus is metabolically diverse, with some lineages thriving in polar and nutrient-rich locations, and other in tropical riverine waters. Although many studies have discussed the ecology and evolution of Synechococcus, there is a paucity of knowledge on the taxonomic structure of SC. Only a few studies have addressed the taxonomy of SC, and this issue still remains largely ignored. Our aim was to establish a new classification system for SC. Our analyses included comparing GC% content, genome size, pairwise Average Amino acid Identity (AAI) values, phylogenomics and gene cluster profiles of 170 publicly available SC genomes. All analyses were consistent with the discrimination of 11 genera, from which 2 are newly proposed (Lacustricoccus and Synechospongium). The new classification is also consistent with the habitat distribution (seawater, freshwater and thermal environments) and reflects the ecological and evolutionary relationships of SC. We provide a practical and consistent classification scheme for the entire Synechococcus collective.

microbiology↗

bioRxiv2020

Unlocking the genomic taxonomy of the Prochloroccus collective

Prochlorococcus is the most abundant photosynthetic prokaryote on our planet. The extensive ecological literature on the Prochlorococcus collective (PC) is based on the assumption that it comprises one single genus comprising the species Prochlorococcus marinus, containing itself a collective of ecotypes. Ecologists adopt the distributed genome hypothesis of an open pan-genome to explain the observed genomic diversity and evolution patterns of the ecotypes within PC. Novel genomic data for the PC prompted us to revisit this group, applying the current methods used in genomic taxonomy. As a result, we were able to distinguish the five genera: Prochlorococcus, Eurycolium, Prolificoccus, Thaumococcus and Riococcus. The novel genera have distinct genomic and ecological attributes.

microbiology↗