Front Microbiol. 2024 Nov 19;15:1466353. doi: 10.3389/fmicb.2024.1466353. eCollection 2024.

ABSTRACT

INTRODUCTION: The advancement of antimicrobial resistance is a significant public health issue today. With the spread of resistant bacterial strains in water resources, especially in urban sewage, metagenomic studies enable the investigation of the microbial composition and resistance genes present in these locations. This study characterized the bacterial community and antibiotic resistance genes in a sewage system that receives effluents from various sources through metagenomics.

METHODS: One liter of surface water was collected at four points of a sewage channel, and after filtration, the total DNA was extracted and then sequenced on an NGS platform (Illumina® NextSeq). The sequenced data were trimmed, and the microbiome was predicted using the Kraken software, while the resistome was analyzed on the CARD webserver. All ecological and statistical analyses were performed using the. RStudio tool.

RESULTS AND DISCUSSION: The complete metagenome results showed a community with high diversity at the beginning and more restricted diversity at the end of the sampling, with a predominance of the phyla Bacteroidetes, Actinobacteria, Firmicutes, and Proteobacteria. Most species were considered pathogenic, with an emphasis on those belonging to the Enterobacteriaceae family. It was possible to identify bacterial groups of different threat levels to human health according to a report by the U.S. Centers for Disease Control and Prevention. The resistome analysis predominantly revealed genes that confer resistance to multiple drugs, followed by aminoglycosides and macrolides, with efflux pumps and drug inactivation being the most prevalent resistance mechanisms. This work was pioneering in characterizing resistance in a sanitary environment in the Amazon region and reinforces that sanitation measures for urban sewage are necessary to prevent the advancement of antibiotic resistance and the contamination of water resources, as evidenced by the process of eutrophication.

PMID:39629213 | PMC:PMC11611572 | DOI:10.3389/fmicb.2024.1466353

Front Oncol. 2024 Nov 19;14:1453202. doi: 10.3389/fonc.2024.1453202. eCollection 2024.

ABSTRACT

INTRODUCTION: The gut microbiome (GM) has been implicated in cancer pathogenesis and treatment, including head and neck cancers (HNC). However, the specific microbial compositions influencing HNC and the underlying mechanisms remain largely unknown.

METHODS: This study utilized published genome-wide association studies (GWAS) summary data-based two-sample Mendelian randomization (MR) to uncover the GM compositions that exert significant causal effects on HNC. Functional annotation and enrichment analysis were conducted to better understand the significant genetic variables and their connection with HNC. The HNC dataset included 2,281 cases and 314,193 controls. The GM GWAS data of 211 gut taxa (35 families, 20 orders, 16 classes, 9 phyla, and 131 genera) were obtained from the MibioGen consortium, involving 18,340 participants.

RESULTS: MR analysis revealed four GM compositions exerting causal effects on HNC. Specifically, family Peptococcaceae.id.2024 was significantly associated with a 35% reduced risk of HNC (OR=0.65; 95%CI=0.48-0.90; P=0.0080). In contrast, genus DefluviitaleaceaeUCG-011.id.11287 (OR=1.54; 95%CI=1.13-2.09; P=0.0060), genus Gordonibacter.id.821 (OR=1.23; 95%CI=1.05-1.45; P=0.012), and genus Methanobrevibacter.id.123 (OR=1.28; 95%CI=1.01-1.62; P=0.040) showed a significant association with an increased risk of HNC. These GMs interact with genes and genetic variants involved in signaling pathways, such as GTPase regulation, influencing tumor progression and disease prognosis.

CONCLUSIONS: Our study demonstrates, for the first time, the causal influence of specific gut microbiome compositions on HNC, offering significant insights for advancing clinical research and personalized treatments. The identified GMs may serve as potential biomarkers or therapeutic targets, paving the way for innovative approaches in HNC diagnosis, prevention, and therapy.

PMID:39628997 | PMC:PMC11611831 | DOI:10.3389/fonc.2024.1453202

Eng Microbiol. 2022 Mar 17;2(2):100013. doi: 10.1016/j.engmic.2022.100013. eCollection 2022 Jun.

ABSTRACT

With the growing demand for air transportation combined with global concerns about environmental issues and the instability and lack of renewability of the oil market, microbial production of high energy density fuels for jets (bio-jet fuels) has received more attention in recent years. Bio-jet fuels can be derived from both isoprenoids and fatty acids, and, additionally, aromatic hydrocarbons derived from expanded shikimate pathways are also candidates for jet fuels. Compared to fatty acid derivatives, most of isoprenoids and aromatic hydrocarbons used for jet fuels have higher density energies. However, they are also highly toxic to host microbes. The cytotoxicity induced during the synthesis of isoprenoid or shikimate pathway-derived biofuels remains one of the major obstacles for industrial production even though synthetic and systems biology approaches have reconstructed and optimized metabolic pathways for production of these bio-jet fuels. Here, we review recent developments in the production of known and potential jet fuels by microorganisms, with a focus on alleviating cytotoxicity caused by the final products, intermediates, and metabolic pathways.

PMID:39628844 | PMC:PMC11611038 | DOI:10.1016/j.engmic.2022.100013

iScience. 2024 Nov 5;27(12):111322. doi: 10.1016/j.isci.2024.111322. eCollection 2024 Dec 20.

ABSTRACT

As single-cell omics data sampling and acquisition methods have accumulated at an unprecedented rate, various data analysis pipelines have been developed for the inference of cell types, cell states and their distribution, state transitions, state trajectories, and state interactions. This presents a new opportunity in which single-cell omics data can be utilized to generate high-resolution, high-fidelity computational models. In this review, we discuss how single-cell omics data can be used to build computational models to simulate biological systems at various scales. We propose that single-cell data can be integrated with physiological information to generate organ-specific models, which can then be assembled to generate multi-organ systems pathophysiological models. Finally, we discuss how generic multi-organ models can be brought to the patient-specific level thus permitting their use in the clinical setting.

PMID:39628578 | PMC:PMC11612781 | DOI:10.1016/j.isci.2024.111322

Appl Plant Sci. 2024 Sep 24;12(6):e11604. doi: 10.1002/aps3.11604. eCollection 2024 Nov-Dec.

ABSTRACT

PREMISE: Common steps in phylogenomic matrix production include biological sequence concatenation, morphological data concatenation, insertion/deletion (indel) coding, gene content (presence/absence) coding, removing uninformative characters for parsimony analysis, recording with reduced amino acid alphabets, and occupancy filtering. Existing software does not accomplish these tasks on a phylogenomic scale using a single program.

METHODS AND RESULTS: BAD2matrix is a Python script that performs the above-mentioned steps in phylogenomic matrix construction for DNA or amino acid sequences as well as morphological data. The script works in UNIX-like environments (e.g., LINUX, MacOS, Windows Subsystem for LINUX).

CONCLUSIONS: BAD2matrix helps simplify phylogenomic pipelines and can be downloaded from https://github.com/dpl10/BAD2matrix/tree/master under a GNU General Public License v2.

PMID:39628543 | PMC:PMC11610412 | DOI:10.1002/aps3.11604

Emerg Microbes Infect. 2024 Dec 4:2437242. doi: 10.1080/22221751.2024.2437242. Online ahead of print.

ABSTRACT

AbstractThe identification of individuals with the greatest risk of progression to active tuberculosis (TB) disease from the huge reservoir of Mycobacterium tuberculosis (Mtb) infected individuals continues to remain an arduous ascent in the global effort to control TB. In a two-year prospective study, we analysed metabolic profiles in the unstimulated and TB antigen stimulated QuantiFERON supernatants of 14 household contacts (HHCs) who progressed to TB (Progressors) and 14 HHCs who remained healthy (Non-Progressors). We identified 21 significantly dysregulated metabolites in the TB antigen-stimulated QuantiFERON supernatants of Progressors, of which the combination of Malic acid and N-Arachidonoylglycine had maximum AUC of 0.99. Eighteen significantly dysregulated metabolites were identified in the unstimulated QuantiFERON supernatants of Progressors, among which the combination of Orotic acid and the phosphatidylcholines PC (O-34:1), PC (O-18:1(9Z)/16:0), PC (O-18:1(11Z)/16:0) had the maximum AUC of 0.98. Most of the dysregulated metabolites belonged to the pathways of fatty acid metabolism, lipid metabolism and nitric oxide metabolism. Validation of these metabolic signatures in large, diverse cohorts would pave way for targetted intervention of TB disease.

PMID:39628384 | DOI:10.1080/22221751.2024.2437242

Microbiome. 2024 Dec 3;12(1):252. doi: 10.1186/s40168-024-01988-6.

NO ABSTRACT

PMID:39627806 | DOI:10.1186/s40168-024-01988-6

Nat Neurosci. 2024 Dec;27(12):2278-2291. doi: 10.1038/s41593-024-01827-9. Epub 2024 Dec 3.

ABSTRACT

Single-cell and single-nucleus genomic approaches can provide unbiased and multimodal insights. Here, we discuss what constitutes a molecular cell atlas and how to leverage single-cell omics data to generate hypotheses and gain insights into cell transitions in development and disease of the nervous system. We share points of reflection on what to consider during study design and implementation as well as limitations and pitfalls.

PMID:39627588 | DOI:10.1038/s41593-024-01827-9

Nat Neurosci. 2024 Dec;27(12):2292-2309. doi: 10.1038/s41593-024-01806-0. Epub 2024 Dec 3.

ABSTRACT

Over the past decade, single-cell genomics technologies have allowed scalable profiling of cell-type-specific features, which has substantially increased our ability to study cellular diversity and transcriptional programs in heterogeneous tissues. Yet our understanding of mechanisms of gene regulation or the rules that govern interactions between cell types is still limited. The advent of new computational pipelines and technologies, such as single-cell epigenomics and spatially resolved transcriptomics, has created opportunities to explore two new axes of biological variation: cell-intrinsic regulation of cell states and expression programs and interactions between cells. Here, we summarize the most promising and robust technologies in these areas, discuss their strengths and limitations and discuss key computational approaches for analysis of these complex datasets. We highlight how data sharing and integration, documentation, visualization and benchmarking of results contribute to transparency, reproducibility, collaboration and democratization in neuroscience, and discuss needs and opportunities for future technology development and analysis.

PMID:39627587 | DOI:10.1038/s41593-024-01806-0

Geroscience. 2024 Dec 3. doi: 10.1007/s11357-024-01449-w. Online ahead of print.

ABSTRACT

Frailty is characterized by loss of physical function and is preferably diagnosed at an early stage (e.g., during pre-frailty). Unfortunately, sensitive tools that can aid early detection are lacking. Blood-based biomarkers, reflecting pathophysiological adaptations before physical symptoms become apparent, could be such tools. We identified candidate biomarkers using a mechanism-based computational approach which integrates a priori defined database-derived clinical biomarkers and skeletal muscle transcriptome data. Identified candidate biomarkers were used as input for a sex-specific correlation analysis, using individual gene expression data from female (n = 24) and male (n = 28) older adults (all 75 + years, ranging from fit to pre-frail) and three frailty-related physical parameters. Male and female groups were matched based on age, BMI, and Fried frailty index. The best correlating candidate biomarkers were evaluated, and selected biomarkers were measured in serum. In females, myostatin and galectin-1 and, in males, cathepsin B and thrombospondin-4 serum levels were significantly different between the physically weakest and fittest participants (all p < 0.05). Logistic regression confirmed the added value of these biomarkers in conjunction with age and BMI to predict whether the subjects belonged to the weaker or fittest group (AUC = 0.80 in females and AUC = 0.83 in males). In conclusion, both in silico and in vivo analyses revealed the sex-specificity of candidate biomarkers, and we identified a selection of potential biomarkers which could be used in a biomarker panel for early detection of frailty. Further investigation is needed to confirm these leads for early detection of frailty.

PMID:39627572 | DOI:10.1007/s11357-024-01449-w

Nat Protoc. 2024 Dec 3. doi: 10.1038/s41596-024-01080-1. Online ahead of print.

ABSTRACT

Tissue clearing, coupled with immunostaining, enables the transition from two-dimensional to three-dimensional pathology and has the potential to substantially improve data quality for biomedical diagnostics. Nevertheless, the workflows are limited by the complex sample processing protocols. Approaches for the parallel processing of samples, to include tissue clearing, immunostaining, imaging and analysis can increase three-dimensional pathology throughput. Here we detail a step-by-step approach that combines a tissue clearing device with a six-well multiwell plate to increase the throughput compared with methods using conventional clearing protocols. The six-well multiplate allows for parallel tissue clearing of multiple samples and is compatible with passive tissue clearing methods including Clear, Unobstructed Brain/Body Imaging Cocktails and Computational (CUBIC) analysis. In addition, gel embedding is performed without moving the samples from the wells, and a series of steps such as imaging with a high-speed light-sheet microscope and analysis in the cloud can be performed. Although this procedure slightly extends the overall time required for preparing and analyzing a single sample, it reduces the effort required at each step, such as reagent exchange and gel embedding, which results in an overall reduction in hands-on time due to the parallel sample processing. We describe a series of whole-organ analyses, including high-throughput tissue clearing, staining, gel embedding, imaging and data analysis in the cloud, as a useful platform for cellular biology and pathology. The total process varies depending on the presence or absence of immunostaining, but for some six-well plates, the tissue clearing process, imaging and data analysis can be completed within 10 d.

PMID:39627541 | DOI:10.1038/s41596-024-01080-1

Nat Commun. 2024 Dec 3;15(1):10512. doi: 10.1038/s41467-024-54985-6.

NO ABSTRACT

PMID:39627221 | DOI:10.1038/s41467-024-54985-6

NPJ Syst Biol Appl. 2024 Dec 4;10(1):144. doi: 10.1038/s41540-024-00472-z.

ABSTRACT

Metastasis is the leading cause of death in patients with cancer, driving considerable scientific and clinical interest in immunosurveillance of micrometastases. We investigated this process by creating a multiscale mathematical model to study the interactions between the immune system and the progression of micrometastases in general epithelial tissue. We analyzed the parameter space of the model using high-throughput computing resources to generate over 100,000 virtual patient trajectories. We demonstrated that the model could recapitulate a wide variety of virtual patient trajectories, including uncontrolled growth, partial response, and complete immune response to tumor growth. We classified the virtual patients and identified key patient parameters with the greatest effect on the simulated immunosurveillance. We highlight the lessons derived from this analysis and their impact on the nascent field of cancer patient digital twins (CPDTs). While CPDTs could enable clinicians to systematically dissect the complexity of cancer in each individual patient and inform treatment choices, our work shows that key challenges remain before we can reach this vision. In particular, we show that there remain considerable uncertainties in immune responses, unreliable patient stratification, and unpredictable personalized treatment. Nonetheless, we also show that in spite of these challenges, patient-specific models suggest strategies to increase control of clinically undetectable micrometastases even without complete parameter certainty.

PMID:39627216 | DOI:10.1038/s41540-024-00472-z

eNeuro. 2024 Dec 3:ENEURO.0487-24.2024. doi: 10.1523/ENEURO.0487-24.2024. Online ahead of print.

ABSTRACT

Delay discounting (DD) is a phenomenon where individuals devalue a reward associated with a temporal delay, with the rate of devaluation being representative of impulsive-like behavior. Here we first sought to develop and validate a mouse DD task to study brain circuits involved in DD decision-making within short developmental time windows, given widespread evidence of developmental regulation of impulse control and risk-taking. We optimized a T-maze DD task for mice that enables training and DD trials within two weeks. Mice learned to choose between a large and a small reward located at opposite arms of a T-maze. Once training criteria were met, mice underwent DD whereby the large reward choice was associated with a temporal delay. Task validation showed that adolescent C57BL/6J mice display increased preference for the small reward upon a temporal delay, confirming increased impulsivity compared to adults. We next used this DD task to explore the neural basis of decision-making. We used tyrosine hydroxylase transgenic mice (TH-Cre) to target TH-positive neurons in the nucleus accumbens (NAc) and ventral tegmental area (VTA) with Cre-dependent excitatory or inhibitory Designer Receptors Exclusively Activated by Designer Drugs (DREADDs). Inhibition of transduced neurons in the NAc decreased preference for the small but immediate reward during DD. Inhibition of TH+ neurons in the ventral tegmental area (VTA) did not affect impulsive choice in this DD task. These results uncover a novel role for NAc TH-positive neurons in DD behavior and expand the repertoire of behavioral tasks available for studying decision-making across the lifespan.Significance Statement Delay discounting (DD) tasks are used in rodents to study impulsive choice, whereby subjects display a preference for an immediate, smaller reward when access to a larger reward is contingent on a temporal delay. Research implicates the nucleus accumbens (NAc) brain region in impulsive behavior, with recent evidence of specialization among NAc neuronal subtypes in impulsive choice. Here we interrogated the neural requirements of impulsive choice in mice. We found that inhibition of a subset of NAc neurons expressing tyrosine hydroxylase decreases impulsive choice. We also saw increased impulsive choice in adolescent mice compared to adults, consistent with reported developmental changes in impulsivity. Together, our data identify cell-specific NAc regulation of impulsive choice with important implications for neurodevelopment.

PMID:39626950 | DOI:10.1523/ENEURO.0487-24.2024

Open Biol. 2024 Dec;14(12):240082. doi: 10.1098/rsob.240082. Epub 2024 Dec 4.

ABSTRACT

Protein quantification is an important tool for a wide range of biological applications. The most common methods include the Lowry, bicinchoninic acid (BCA) and Coomassie Bradford assays. Despite their wide applicability, the mechanisms of action imply that these methods may not be ideal for large transmembrane proteins due to the proteins' integration in the plasma membrane. Here, we investigate this problem by assessing the efficacy and applicability of these three common protein quantification methods on a candidate transmembrane protein: Na, K-ATPase (NKA). We compared these methods with an ELISA, which we newly developed and describe here for the quantification of NKA. The use of a relative standard curve allows this ELISA to be easily adapted to other proteins and across the animal kingdom. Our results revealed that the three conventional methods significantly overestimate the concentration of NKA compared with the ELISA. This is due to the samples containing a heterogeneous mix of proteins, including a significant amount of non-target proteins. Further, by applying the protein concentrations determined by the different methods to in vitro assays, we found that variation in the resulting data was consistently low when the assay reactions were prepared based on concentrations determined from the ELISA.

PMID:39626776 | DOI:10.1098/rsob.240082

Cell Genom. 2024 Nov 27:100701. doi: 10.1016/j.xgen.2024.100701. Online ahead of print.

ABSTRACT

Identifying the molecular effects of human genetic variation across cellular contexts is crucial for understanding the mechanisms underlying disease-associated loci, yet many cell types and developmental stages remain underexplored. Here, we harnessed the potential of heterogeneous differentiating cultures (HDCs), an in vitro system in which pluripotent cells asynchronously differentiate into a broad spectrum of cell types. We generated HDCs for 53 human donors and collected single-cell RNA sequencing data from over 900,000 cells. We identified expression quantitative trait loci in 29 cell types and characterized regulatory dynamics across diverse differentiation trajectories. This revealed novel regulatory variants for genes involved in key developmental and disease-related processes while replicating known effects from primary tissues and dynamic regulatory effects associated with a range of complex traits.

PMID:39626676 | DOI:10.1016/j.xgen.2024.100701

Mol Cell. 2024 Nov 19:S1097-2765(24)00861-X. doi: 10.1016/j.molcel.2024.10.021. Online ahead of print.

ABSTRACT

Although critical for tuning the timing and level of transcription, enhancer communication with distal promoters is not well understood. Here, we bypass the need for sequence-specific transcription factors (TFs) and recruit activators directly using a chimeric array of gRNA oligos to target dCas9 fused to the activator VP64-p65-Rta (CARGO-VPR). We show that this approach achieves effective activator recruitment to arbitrary genomic sites, even those inaccessible when targeted with a single guide. We utilize CARGO-VPR across the Prdm8-Fgf5 locus in mouse embryonic stem cells (mESCs), where neither gene is expressed. Although activator recruitment to any tested region results in the transcriptional induction of at least one gene, the expression level strongly depends on the genomic distance between the promoter and activator recruitment site. However, the expression-distance relationship for each gene scales distinctly in a manner not attributable to differences in 3D contact frequency, promoter DNA sequence, or the presence of repressive chromatin marks at the locus.

PMID:39626660 | DOI:10.1016/j.molcel.2024.10.021

Dev Cell. 2024 Dec 2;59(23):3059-3060. doi: 10.1016/j.devcel.2024.09.019.

ABSTRACT

In this issue of Developmental Cell, Zhang et al. report that secreted PTEN reprograms immunosuppressive tumor-associated macrophages into an inflammatory phenotype by binding to PLXDC2, which enhances antitumor immunity. This Preview discusses diverse functions of PTEN in the nucleus, cytoplasm, and extracellular matrix, highlighting its multifaceted roles in cancer.

PMID:39626634 | DOI:10.1016/j.devcel.2024.09.019

Elife. 2024 Dec 3;13:e88231. doi: 10.7554/eLife.88231.

ABSTRACT

Over the last three decades, human genetics has gone from dissecting high-penetrance Mendelian diseases to discovering the vast and complex genetic etiology of common human diseases. In tackling this complexity, scientists have discovered the importance of numerous genetic processes - most notably functional regulatory elements - in the development and progression of these diseases. Simultaneously, scientists have increasingly used multiplex assays of variant effect to systematically phenotype the cellular consequences of millions of genetic variants. In this article, we argue that the context of genetic variants - at all scales, from other genetic variants and gene regulation to cell biology to organismal environment - are critical components of how we can employ genomics to interpret these variants, and ultimately treat these diseases. We describe approaches to extend existing experimental assays and computational approaches to examine and quantify the importance of this context, including through causal analytic approaches. Having a unified understanding of the molecular, physiological, and environmental processes governing the interpretation of genetic variants is sorely needed for the field, and this perspective argues for feasible approaches by which the combined interpretation of cellular, animal, and epidemiological data can yield that knowledge.

PMID:39625477 | DOI:10.7554/eLife.88231

Mol Ecol. 2024 Dec 3:e17596. doi: 10.1111/mec.17596. Online ahead of print.

ABSTRACT

Symbiotic marine bacteria that are transmitted through the environment are susceptible to abiotic factors (salinity, temperature, physical barriers) that can influence their ability to colonize their specific hosts. Given that many symbioses are driven by host specificity, environmentally transmitted symbionts are more susceptible to extrinsic factors depending on conditions over space and time. In order to determine whether the population structure of environmentally transmitted symbionts reflects host specificity or biogeography, we analysed the genetic structure of Sepiola atlantica (Cephalopoda: Sepiolidae) and their Vibrio symbionts (V. fischeri and V. logei) in four Galician Rías (Spain). This geographical location is characterized by a jagged coastline with a deep-sea entrance into the land, ideal for testing whether such population barriers exist due to genetic isolation. We used haplotype estimates combined with nested clade analysis to determine the genetic relatedness for both S. atlantica and Vibrio bacteria. Analyses of molecular variance (AMOVA) were used to estimate variation within and between populations for both host and symbiont genetic data. Our analyses reveal a low percentage of variation among and between host populations, suggesting that these populations are panmictic. In contrast, Vibrio symbiont populations show certain degree of genetic structure, demonstrating that the hydrology of the rías is driving bacterial distribution (and not host specificity). Thus, for environmentally transmitted symbioses such as the sepiolid squid-Vibrio association, abiotic factors can be a major selective force for determining population structure for one of the partners.

PMID:39625066 | DOI:10.1111/mec.17596