Biology subjects

Garza, D. R.

Publications and source records attributed to Garza, D. R..

8 recordsLinked to original sources

bioRxiv2025

Chemistry-based vectors map the chemical space of natural biomes from untargeted mass spectrometry data

Untargeted metabolomics can comprehensively map the chemical space of a biome, but is limited by low annotation rates (<10%). We used chemistry-based vectors, consisting of molecular fingerprints or chemical compound classes, predicted from mass spectrometry data, to characterize compounds and samples. These chemical characteristics vectors (CCVs) estimate the fraction of compounds with specific chemical properties in a sample. Unlike the aligned MS1 data with intensity information, CCVs incorporate actual chemical properties of compounds, offering deeper insights into sample comparisons. Thus, we identified key compound classes differentiating biomes, such as ethers which are enriched in environmental biomes, while steroids enriched in animal host-related biomes. In biomes with greater variability, CCVs revealed key clustering compound classes, such as organonitrogen compounds in animal distal gut and lipids in animal secretions. CCVs thus enhance the interpretation of untargeted metabolomic data, providing a quantifiable and generalizable understanding of the chemical space of natural biomes.

bioinformatics↗

bioRxiv2024

Discovery of alternative stable states in a synthetic human gut microbial community

AbstractSeveral human-associated microbial communities exist in multiple configurations and can change their composition in response to perturbations, remaining in an altered state even after the perturbation ends. Multistability has been previously proposed to explain this behavior for gut microbiota in particular, but has not been clearly demonstrated experimentally. Here, we first investigated the life history strategies of three common human gut bacteria to identify mechanisms driving alternative states. We then used this data to build and parameterize a kinetic model, which predicted that alternative states emerge due to phenotype switching between subpopulations of the same species. Perturbation experiments supported these predictions, and confirmed the existence of alternative states. Finally, simulations showed that phenotype switching can also explain alternative states in larger communities. Thus, a transient perturbation combined with metabolic flexibility is sufficient for alternative communities to emerge, implying that they are not necessarily explained by differences between individuals. One-Sentence SummaryWe demonstrate the existence of alternative states in a human gut microbial community and propose phenotype switching as a mechanism explaining their emergence.

microbiology↗

bioRxiv2023

Starvation response strategies of human gut bacteria Bacteroides thetaiotaomicron and Roseburia intestinalis and their impact on co-culture dynamics

Bacterial growth often alters the environment, which in turn can impact interspecies interactions among bacteria. Here, we used an in vitro batch system containing mucin beads to emulate the dynamic host environment and to study its impact on the interactions between two abundant and prevalent human gut bacteria, the primary fermenter Bacteroides thetaiotaomicron and the butyrate producer Roseburia intestinalis. By combining machine learning and flow cytometry, we found that the number of viable B. thetaiotaomicron cells decreases with glucose consumption due to acid production, while R. intestinalis survives post-glucose depletion by entering a slow growth mode. Both species attach to mucin beads, but only viable cell counts of B. thetaiotaomicron increase significantly. The number of viable co-culture cells varies significantly over time compared to those of monocultures. A combination of targeted metabolomics and RNA-seq showed that the slow growth mode of R. intestinalis represents a diauxic shift towards acetate and lactate consumption, whereas B. thetaiotaomicron survives glucose depletion and low pH by foraging on mucin sugars. In addition, most of the mucin monosaccharides we tested inhibited the growth of R. intestinalis but not B. thetaiotaomicron. We encoded these causal relationships in a kinetic model, which reproduced the observed dynamics. In summary, we explored how R. intestinalis and B. thetaiotaomicron respond to nutrient scarcity and how this affects their dynamics. We highlight the importance of understanding bacterial metabolic strategies to effectively modulate microbial dynamics in changing conditions.

microbiology↗

bioRxiv2022

Characterization of Genomic Diversity In Bacteriophages Infecting Rhodococcus

Bacteriophages are globally ubiquitous viruses that infect bacteria. With nearly 4,000 sequenced genomes of phages infecting the phylum Actinobacteria available, genomic analyses of these actinobacteriophage genomes has been instrumental in uncovering a diverse genomic landscape often characterized by genome mosaicism. Here, we describe the genomic characterization of 57 sequenced phages capable of infecting the genus Rhodococcus. These phages were previously isolated at multiple institutions by students in the SEA-PHAGES program using four different species of Rhodococcus. Most Rhodococcus phages have been grouped into 4 clusters based on their genomic similarities; 13 phages are singletons too genetically distinct for clustering. These clusters and singletons contain Siphoviridae and Myoviridae phages, and most contain integrase and repressor genes indicative of a potential lysogenic life cycle. The genome size of these phages varies from 14,270 bp to 142,586 bp and their G+C% content ranges from 41.2-68.4%, while that of their Rhodococcus hosts typically exceeds 60%. Through comparative genomic analyses, it was revealed that these Rhodococcus phages display high intracluster similarity but low intercluster similarity, despite their shared ability to infect the same host genus. Additionally, these Rhodococcus phages share similarities with phages that infect other Actinobacterial hosts such as Gordonia, Streptomyces and Arthrobacter.

microbiology↗

bioRxiv2021

A prioritized and validated resource of mitochondrial proteins in Plasmodium identifies leads to unique biology

Plasmodium species have a single mitochondrion that is essential for their survival and has been successfully targeted by anti-malarial drugs. Most mitochondrial proteins are imported into this organelle and our picture of the Plasmodium mitochondrial proteome remains incomplete. Many data sources contain information about mitochondrial localization, including proteome and gene expression profiles, orthology to mitochondrial proteins from other species, co-evolutionary relationships, and amino acid sequences, each with different coverage and reliability. To obtain a comprehensive, prioritized list of Plasmodium falciparum mitochondrial proteins, we rigorously analyzed and integrated eight datasets using Bayesian statistics into a predictive score per protein for mitochondrial localization. At a corrected false discovery rate of 25%, we identified 445 proteins with a sensitivity of 87% and a specificity of 97%. They include proteins that have not been identified as mitochondrial in other eukaryotes but have characterized homologs in bacteria that are involved in metabolism or translation. Mitochondrial localization of seven Plasmodium berghei orthologs was confirmed by epitope labeling and co-localization with a mitochondrial marker protein. One of these belongs to a newly identified apicomplexan mitochondrial protein family that in P. falciparum has four members. With the experimentally validated mitochondrial proteins and the complete ranked P. falciparum proteome, which we have named PlasmoMitoCarta, we present a resource to study unique proteins of Plasmodium mitochondria.

bioinformatics↗

bioRxiv2020

Nutrition or nature: disentangling the complex forces shaping prokaryote pan-genomes

Microbial pan-genomes are shaped by a complex combination of stochastic and deterministic forces. Even closely related genomes often exhibit extensive variation in their gene content. Understanding what drives this variation requires exploring the interactions of genes with each other and with their external environments. However, to date, conceptual models of pan-genome dynamics often represent genes as independent units and provide limited information about their mechanistic interactions. Here, we use pan-reactomes as proxies for pan-genomes since they can explicitly represent the interactions between the genes that code for metabolic reactions and simulate complex phenotypes that interact with the metabolic environment. We interpreted pan-reactomes as dynamic pools of metabolic reactions that are potentially gained or lost and simulated the routes along which different lineages lose reactions in alternative environments. We performed these simulations on the pan-reactomes of 46 bacterial and archaeal families covering a broad taxonomic range. These simulations allowed us to disentangle metabolic reactions whose presence does, and does not depend on the metabolite composition of the external environment, allowing us to identify reactions constrained "by nutrition" and "by nature", respectively. By comparing the frequency of reactions from the first group with their observed frequencies in bacterial and archaeal families, we predicted the metabolic niches that shaped the genomic composition of these lineages in their evolutionary past. Moreover, we found that the lineages that were shaped by a more diverse metabolic niche also occur in more diverse biomes as assessed by global environmental sequencing datasets. Together, we introduce a computational framework for analyzing and interpreting pan-reactomes that provides new insights into the ecological and evolutionary drivers of pan-genome composition.

evolutionary biology↗

bioRxiv2020

Optimized DNA isolation method for microbiome analysis of human tissues

Recent advances in microbiome sequencing have rendered new insights into the role of the microbiome in human health with potential clinical implications. Unfortunately, developments in the field of tissue microbiomes have been hampered by the presence of host DNA in isolates which interferes with the analysis of the bacterial content. Here, we present a DNA isolation protocol from tissue samples including reduction of host DNA without distortion of microbial abundance profiles. We evaluated which concentrations of Triton and saponin lyse host cells and leave bacterial cells intact, which was combined with DNAse treatment to deplete released host DNA. We applied our protocol to extract microbial DNA from ex vivo and in vivo acquired human colon biopsies ([~]2-5 mm in size) and assessed the relative abundance of bacterial and human DNA by qPCR. Saponin at a concentration of 0.0125% in PBS lysed host cells, resulting in a 4.5-fold enrichment of bacterial DNA while preserving the relative abundance of Firmicutes, Bacteroidetes, {gamma}-Proteobacteria and Actinobacteria. Our protocol combined with shotgun metagenomic sequencing revealed a colon tissue microbiome profile with a Shannon diversity index of 3.2 and an UniFrac distance of 0.54, which is comparable to reported numbers based on amplicon sequencing. Hereby, we present the first protocol for enriching bacterial DNA from tissue biopsies that allows efficient isolation of rigid Gram-positive bacteria without depleting the more sensitive Gram-negative bacteria. Our protocol facilitates analysis of a wide spectrum of bacteria of clinical tissue samples improving their applicability for microbiome research.

microbiology↗

bioRxiv2019

Growth rate alterations of human colorectal cancer cells by 157 gut bacteria

Several bacteria in the human gut microbiome have been associated with colorectal cancer (CRC) by high-throughput screens. In some cases, molecular mechanisms have been elucidated that drive tumorigenesis, including bacterial membrane proteins or secreted molecules that interact with the human cancer cells. For most gut bacteria, however, it remains unknown if they enhance or inhibit cancer cell growth. Here, we screened bacteria-free supernatants (secretomes) and inactivated cells of over 150 cultured bacterial strains for their effect on CRC cell growth. We observed family-level and strain-level effects that often differed between bacterial cells and secretomes, suggesting that different molecular mechanisms are at play. Secretomes of Bacteroidaceae, Enterobacteriaceae, and Erysipelotrichaceae bacteria enhanced CRC cell growth, while most Fusobacteriaceae cells and secretomes inhibited growth, contrasting prior findings. In some bacteria, the presence of specific functional genes was associated with CRC cell growth rates, including the virulence genes TcdA in Clostridiales and FadA in Fusobacteriaceae, which both inhibited growth. Bacteroidaceae cells that enhanced growth were enriched for genes of the cobalamin synthesis pathway, while Fusobacteriaceae cells that inhibit growth were enriched for genes of the ethanolamine utilization pathway. Together, our results reveal how different gut bacteria have wide-ranging effects on cancer cells, contribute a better understanding of the effects of the gut microbiome on the human host, and provide a valuable resource for identifying candidate target genes for potential microbiome-based diagnostics and treatment strategies.

microbiology↗