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

Front Pharmacol. 2024 Nov 18;15:1453989. doi: 10.3389/fphar.2024.1453989. eCollection 2024.

ABSTRACT

INTRODUCTION: Treatment of rodents with the AT1 blocker (ARB) telmisartan (TEL) has an anti-adipose effect. Among other mechanisms, we also have attributed the anti-adipose action to diet-independent alterations in gut microbiota. Thus, we aimed here to confirm this mechanism by using the fecal microbiota transfer (FMT) approach.

METHODS: Seven weeks after initiating a high-fat diet (HFD), C57BL/6N mice received fecal microbiota for 8 weeks from donor mice by oral gavage, continuing HFD feeding. Stool samples came from mice that were treated with TEL (8 mg/kg/d by gavage, 12 weeks), thus remaining lean despite HFD feeding (BL/6>fTEL), while controls received feces samples from vehicle/HFD-treated obese mice (BL/6>fVEH). Microbiota of the stool samples from these acceptor mice was analyzed by 16S rRNA gene amplicon sequencing.

RESULTS: Weight gain was lower in BL6>fTEL than in BL6>fVEH mice after 3 but not 8 weeks. Energy homeostasis, insulin sensitivity, and body composition did not differ between the two groups. β-diversity indicated group differences (F = 2.27, p = 0.005). Although the Firmicutes/Bacteroides ratio did not differ, abundances of distinct phyla, families, and genera varied. Among others, Ruminococcaceae and Desulfovibrionaceae, Desulfovibrionia uncl., and Lachnospiraceae uncl. were lower in BL/6>fTEL than in BL/6>fVEH mice. Moreover, the correlation between body weight and Lachnospiraceae, Desulfovibrionaceae, Desulfovibrionia uncl., or Desulfovibrio was positive in BL/6>fVEH and negative in BL/6>fTEL mice.

DISCUSSION: As FMT from TEL-pretreated mice influences the microbiota in acceptor mice with slight weight-reducing effects, we confirm the relevance of TEL-related microbiota changes for weight reduction, most likely independent of the transferred stool-residual TEL effect on the host metabolism.

PMID:39624839 | PMC:PMC11608989 | DOI:10.3389/fphar.2024.1453989

Heliyon. 2024 Nov 8;10(22):e39920. doi: 10.1016/j.heliyon.2024.e39920. eCollection 2024 Nov 30.

ABSTRACT

This study employed a comprehensive genome-mining approach to characterize CRISPR-Cas systems in Lactobacillus delbrueckii strains. The analysis involved retrieving 105 genome sequences to explore the variety, occurrence, and evolution of CRISPR-Cas systems within the species. Homology analysis of spacer sequences in detected CRISPR arrays was conducted to assess the variety of target phages and plasmids. The evolutionary trajectories of spaceromes in each subtype of CRISPR arrays were determined by analyzing acquisition and deletion events under the selection pressure of foreign plasmids and phages. Among the analyzed strains, 53 contained only one CRISPR-Cas locus, 11 had two loci, and 21 featured three loci with complete CRISPR-Cas systems. Subtype designation of the results of current study revealed that 56 % of these systems belong to subtypes I-E/I-C, 23 % to subtypes III-A/III-D, and 17 % to subtype II-A. Notably, certain plasmids were found to be specifically targeted by distinct CRISPR array systems. The comparison of spacer sequences with phage genomes indicated that strains containing only CRISPR-Cas type-I systems targeted a broader range of phages. In conclusion, this study highlights the diversity of the three identified CRISPR-Cas types in L. delbrueckii strains and emphasizes their significant role in defense against phage invasion.

PMID:39624314 | PMC:PMC11609665 | DOI:10.1016/j.heliyon.2024.e39920

Front Plant Sci. 2024 Nov 14;15:1465030. doi: 10.3389/fpls.2024.1465030. eCollection 2024.

ABSTRACT

Terpenoids are valued chemicals in the pharmaceutical, biotechnological, cosmetic, and biomedical industries. Biosynthesis of these chemicals relies on polymerization of Isopentenyl di-phosphate (IPP) and/or dimethylallyl diphosphate (DMAPP) monomers, which plants synthesize using a cytosolic mevalonic acid (MVA) pathway and a plastidic methyleritritol-4-phosphate (MEP) pathway. Circadian regulation affects MVA and MEP pathway activity at three levels: substrate availability, gene expression of pathway enzymes, and utilization of IPP and DMAPP for synthesizing complex terpenoids. There is a gap in understanding the interplay between the circadian rhythm and the dynamics and regulation of the two pathways. In this paper we create a mathematical model of the MVA and MEP pathways in plants that incorporates the effects of circadian rhythms. We then used the model to investigate how annual and latitudinal variations in circadian rhythm affect IPP and DMAPP biosynthesis. We found that, despite significant fluctuations in daylight hours, the amplitude of oscillations in IPP and DMAPP concentrations remains stable, highlighting the robustness of the system. We also examined the impact of removing circadian regulation from different parts of the model on its dynamic behavior. We found that regulation of pathway substrate availability alone results in higher sensitivity to daylight changes, while gene expression regulation alone leads to less robust IPP/DMAPP concentration oscillations. Our results suggest that the combined circadian regulation of substrate availability, gene expression, and product utilization, along with MVA- and MEP-specific regulatory loops, create an optimal operating regime. This regime maintains pathway flux closely coupled to demand and stable across a wide range of daylight hours, balancing the dynamic behavior of the pathways and ensuring robustness in response to cellular demand for IPP/DMAPP.

PMID:39624244 | PMC:PMC11609946 | DOI:10.3389/fpls.2024.1465030

Front Plant Sci. 2024 Nov 18;15:1397632. doi: 10.3389/fpls.2024.1397632. eCollection 2024.

ABSTRACT

Canola (Brassica napus L.) is a valuable oilseed crop worldwide. However, trait improvement by breeding has been limited by its low genetic diversity and polyploid genetics. Whilst offering many potential benefits, the application of transgenic technology is challenged by the stringent and expensive regulatory processes associated with the commercialisation of genetically modified organisms, coupled with a prevailing low public acceptance of such modifications. DNA-free genome editing using Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas9 ribonucleoproteins (RNPs) offers a promising way to achieve trait improvements without the limitations of transgenic methods. Here, we present a method for DNA-free genome editing via the direct delivery of RNPs to canola mesophyll protoplasts. This method allows high-throughput in vivo testing of the efficacy of gRNA design as part of the transformation process to facilitate the selection of optimal designs prior to the generation of edited events. Of the 525 shoots regenerated via tissue culture from RNP-transfected protoplasts and screened for the presence of mutations in the targeted gene, 62% had one or more mutated target alleles, and 50% had biallelic mutations at both targeted loci. This high editing efficiency compares favourably with similar CRISPR-Cas9 approaches used in other crop plants.

PMID:39624242 | PMC:PMC11608969 | DOI:10.3389/fpls.2024.1397632

Comput Struct Biotechnol J. 2024 Nov 13;23:4108-4123. doi: 10.1016/j.csbj.2024.11.013. eCollection 2024 Dec.

ABSTRACT

Cancer is the second leading cause of disease-related death worldwide, and machine learning-based identification of novel biomarkers is crucial for improving early detection and treatment of various cancers. A key challenge in applying machine learning to high-dimensional data is deriving important features in an interpretable manner to provide meaningful insights into the underlying biological mechanisms We developed a class-based directional feature importance (CLIFI) metric for decision tree methods and demonstrated its use for The Cancer Genome Atlas proteomics data. The CLIFI metric was incorporated into four algorithms, Random Forest (RF), LAtent VAriable Stochastic Ensemble of Trees (LAVASET), and Gradient Boosted Decision Trees (GBDTs), and a new extension incorporating the LAVA step into GBDTs (LAVABOOST). Both LAVA methods incorporate topological information from protein interactions into the decision function. The different models' performance in classifying 28 cancers resulted in F1-scores of 92.6% (RF), 92.0% (LAVASET), 89.3% (LAVABOOST) and 85.7% (GBDT), with no method outperforming all others for individual cancer type prediction. The CLIFI metric enables visualisation of the model's decision-making functions. The resulting CLIFI value distributions indicated heterogeneity in the expression of several proteins (MYH11, ERα, BCL2) across different cancer types (including brain glioma, breast, kidney, thyroid and prostate cancer) aligning with the original raw expression data. In conclusion, we have developed an integrated, directional feature importance metric for multi-class decision tree-based classification models that facilitates interpretable feature importance assessment. The CLIFI metric can be combined with incorporating topological information into the decision functions of models to introduce inductive bias, enhancing interpretability.

PMID:39624167 | PMC:PMC11609472 | DOI:10.1016/j.csbj.2024.11.013

Small Methods. 2024 Dec 2:e2401163. doi: 10.1002/smtd.202401163. Online ahead of print.

ABSTRACT

Spatially Resolved Transcriptomics (SRT) offers unprecedented opportunities to elucidate the cellular arrangements within tissues. Nevertheless, the absence of deconvolution methods that simultaneously model multi-modal features has impeded progress in understanding cellular heterogeneity in spatial contexts. To address this issue, SpaDA is developed, a novel spatially aware domain adaptation method that integrates multi-modal data (i.e., transcriptomics, histological images, and spatial locations) from SRT to accurately estimate the spatial distribution of cell types. SpaDA utilizes a self-expressive variational autoencoder, coupled with deep spatial distribution alignment, to learn and align spatial and graph representations from spatial multi-modal SRT data and single-cell RNA sequencing (scRNA-seq) data. This strategy facilitates the transfer of cell type annotation information across these two similarity graphs, thereby enhancing the prediction accuracy of cell type composition. The results demonstrate that SpaDA surpasses existing methods in cell type deconvolution and the identification of cell types and spatial domains across diverse platforms. Moreover, SpaDA excels in identifying spatially colocalized cell types and key marker genes in regions of low-quality measurements, exemplified by high-resolution mouse cerebellum SRT data. In conclusion, SpaDA offers a powerful and flexible framework for the analysis of multi-modal SRT datasets, advancing the understanding of complex biological systems.

PMID:39623794 | DOI:10.1002/smtd.202401163

Microbiome. 2024 Dec 2;12(1):251. doi: 10.1186/s40168-024-01971-1.

ABSTRACT

BACKGROUND: Osteosarcopenia, characterized by the simultaneous loss of bone and muscle mass, is a serious health problem in the aging population. This study investigated the interplay between host genetics, gut microbiota, and musculoskeletal health in a mouse model of osteosarcopenia, exploring the therapeutic potential of gut microbiota modulation.

METHODS: We examined the effects of Rg3, a phytochemical, on osteosarcopenia and its interactions with host genetics and gut microbiota in six founder strains of the Collaborative Cross (CC) population. Subsequently, we evaluated the therapeutic potential of Eubacterium nodatum (EN) and Eubacterium ventriosum (EV), two gut microbes identified as significant correlates of Rg3-mediated osteosarcopenia improvement, in selected C57BL/6 J (B6) and 129S1/SvImJ (129S1) mouse strains.

RESULTS: Rg3 treatment altered gut microbiota composition aligned with osteosarcopenia phenotypes, which response varied depending on host genetics. This finding enabled the identification of two microbes in the Eubacterium genus, potential mediator of Rg3 effect on osteosarcopenia. Oral administration of EN and EV differentially impacted bone density, muscle mass, exercise performance, and related gene expression in a mouse strain-specific manner. In 129S1 mice, EN and EV significantly improved these parameters, effectively reversing osteosarcopenic phenotypes. Mechanistic investigations revealed that these effects were mediated through the modulation of osteoblast differentiation and protein degradation pathways. In contrast, EN and EV did not significantly improve osteosarcopenic phenotypes in B6 mice, although they did modulate mitochondrial biogenesis and microbial diversity.

CONCLUSIONS: Our findings underscore the complex interplay between host genetics and the gut microbiota in osteosarcopenia and emphasize the need for personalized treatment strategies. EN and EV exhibit strain-specific therapeutic effects, suggesting that tailoring microbial interventions to individual genetic backgrounds may be crucial for optimizing treatment outcomes. Video Abstract.

PMID:39623488 | DOI:10.1186/s40168-024-01971-1

Nat Microbiol. 2024 Dec 2. doi: 10.1038/s41564-024-01857-w. Online ahead of print.

ABSTRACT

By acquiring or evolving resistance to one antibiotic, bacteria can become cross-resistant to a second antibiotic, which further limits therapeutic choices. In the opposite scenario, initial resistance leads to collateral sensitivity to a second antibiotic, which can inform cycling or combinatorial treatments. Despite their clinical relevance, our knowledge of both interactions is limited. We used published chemical genetics data of the Escherichia coli single-gene deletion library in 40 antibiotics and devised a metric that discriminates between known cross-resistance and collateral-sensitivity antibiotic interactions. Thereby we inferred 404 cases of cross-resistance and 267 of collateral-sensitivity, expanding the number of known interactions by over threefold. We further validated 64/70 inferred interactions using experimental evolution. By identifying mutants driving these interactions in chemical genetics, we demonstrated that a drug pair can exhibit both interactions depending on the resistance mechanism. Finally, we applied collateral-sensitive drug pairs in combination to reduce antibiotic-resistance development in vitro.

PMID:39623067 | DOI:10.1038/s41564-024-01857-w

Nat Immunol. 2024 Dec 2. doi: 10.1038/s41590-024-02046-x. Online ahead of print.

NO ABSTRACT

PMID:39622949 | DOI:10.1038/s41590-024-02046-x