Nat Commun. 2023 Dec 7;14(1):8106. doi: 10.1038/s41467-023-43632-1.

ABSTRACT

Small noncoding RNAs (sRNAs) are crucial regulators of gene expression in bacteria. Acting in concert with major RNA chaperones such as Hfq or ProQ, sRNAs base-pair with multiple target mRNAs and form large RNA-RNA interaction networks. To systematically investigate the RNA-RNA interactome in living cells, we have developed a streamlined in vivo approach iRIL-seq (intracellular RIL-seq). This generic approach is highly robust, illustrating the dynamic sRNA interactomes in Salmonella enterica across multiple stages of growth. We have identified the OmpD porin mRNA as a central regulatory hub that is targeted by a dozen sRNAs, including FadZ cleaved from the conserved 3'UTR of fadBA mRNA. Both ompD and FadZ are activated by CRP, constituting a type I incoherent feed-forward loop in the fatty acid metabolism pathway. Altogether, we have established an approach to profile RNA-RNA interactomes in live cells, highlighting the complexity of RNA regulatory hubs and RNA networks.

PMID:38062076 | DOI:10.1038/s41467-023-43632-1

Cell Rep. 2023 Dec 5;42(12):113525. doi: 10.1016/j.celrep.2023.113525. Online ahead of print.

ABSTRACT

Estrogen-dependent proliferation followed by progesterone-dependent differentiation of the endometrium culminates in a short implantation window. We performed single-cell assay for transposase-accessible chromatin with sequencing on endometrial samples obtained across the menstrual cycle to investigate the regulation of temporal gene networks that control embryo implantation. We identify uniquely accessible chromatin regions in all major cellular constituents of the endometrium, delineate temporal patterns of coordinated chromatin remodeling in epithelial and stromal cells, and gain mechanistic insights into the emergence of a receptive state through integrated analysis of enriched transcription factor (TF) binding sites in dynamic chromatin regions, chromatin immunoprecipitation sequencing analyses, and gene expression data. We demonstrate that the implantation window coincides with pervasive cooption of transposable elements (TEs) into the regulatory chromatin landscape of decidualizing cells and expression of TE-derived transcripts in a spatially defined manner. Our data constitute a comprehensive map of the chromatin changes that control TF activities in a cycling endometrium at cellular resolution.

PMID:38060448 | DOI:10.1016/j.celrep.2023.113525

STAR Protoc. 2023 Dec 6;4(4):102706. doi: 10.1016/j.xpro.2023.102706. Online ahead of print.

ABSTRACT

Here, we present a protocol for generating gene-specific split-GAL4 drivers from coding intronic Minos-mediated integration cassette/CRISPR-mediated integration cassette (MiMIC/CRIMIC) lines in Drosophila. We describe steps for four rounds of in vivo genetic crosses, PCR genotyping, and fluorescence imaging to ensure correct orientation of split-GAL4 integration before establishing stable fly stocks. This protocol offers a cost-effective alternative to traditional microinjection techniques for converting coding intronic MiMIC/CRIMIC lines into gene-specific split-GAL4 lines that are adaptable for fly researchers working on different tissues. For complete details on the use and execution of this protocol, please refer to Chen et al.1.

PMID:38060386 | DOI:10.1016/j.xpro.2023.102706

Elife. 2023 Dec 7;12:e94382. doi: 10.7554/eLife.94382.

ABSTRACT

A deep analysis of multiple genomic datasets reveals which genetic pathways associated with atherosclerosis and coronary artery disease are shared between mice and humans.

PMID:38060304 | DOI:10.7554/eLife.94382

Elife. 2023 Dec 7;12:RP88266. doi: 10.7554/eLife.88266.

ABSTRACT

Mouse models have been used extensively to study human coronary artery disease (CAD) or atherosclerosis and to test therapeutic targets. However, whether mouse and human share similar genetic factors and pathogenic mechanisms of atherosclerosis has not been thoroughly investigated in a data-driven manner. We conducted a cross-species comparison study to better understand atherosclerosis pathogenesis between species by leveraging multiomics data. Specifically, we compared genetically driven and thus CAD-causal gene networks and pathways, by using human GWAS of CAD from the CARDIoGRAMplusC4D consortium and mouse GWAS of atherosclerosis from the Hybrid Mouse Diversity Panel (HMDP) followed by integration with functional multiomics human (STARNET and GTEx) and mouse (HMDP) databases. We found that mouse and human shared >75% of CAD causal pathways. Based on network topology, we then predicted key regulatory genes for both the shared pathways and species-specific pathways, which were further validated through the use of single cell data and the latest CAD GWAS. In sum, our results should serve as a much-needed guidance for which human CAD-causal pathways can or cannot be further evaluated for novel CAD therapies using mouse models.

PMID:38060277 | DOI:10.7554/eLife.88266

Methods Mol Biol. 2024;2745:233-253. doi: 10.1007/978-1-0716-3577-3_15.

ABSTRACT

In essence, the COVID-19 pandemic can be regarded as a systems biology problem, with the entire world as the system, and the human population as the element transitioning from one state to another with certain transition rates. While capturing all the relevant features of such a complex system is hardly possible, compartmental epidemiological models can be used as an appropriate simplification to model the system's dynamics and infer its important characteristics, such as basic and effective reproductive numbers of the virus. These measures can later be used as response variables in feature selection methods to uncover the main factors contributing to disease transmissibility. We here demonstrate that a combination of dynamic modeling and machine learning approaches can represent a powerful tool in understanding the spread, not only of COVID-19, but of any infectious disease of epidemiological proportions.

PMID:38060190 | DOI:10.1007/978-1-0716-3577-3_15

Methods Mol Biol. 2024;2745:211-225. doi: 10.1007/978-1-0716-3577-3_13.

ABSTRACT

Epithelial-mesenchymal transition (EMT) is a trans-differentiating and reversible process that leads to dramatic cell phenotypic changes, enabling epithelial cells in acquiring mesenchymal phenotypes and behaviors. EMT plays a crucial role during embryogenesis, and occurs in several para-physiologic and pathological conditions, as during fibrosis or cancer development. EMT displays some hallmarks of critical transitions, as a sudden change in the overall configuration of a system in correspondence of specific tipping point around which a "catastrophic bifurcation" happens. The transition occurs when external conditions breach specific thresholds. This definition helps in highlighting two main aspects: (1) the change involves the overall system, rather than single, discrete components; (2) cues from the microenvironment play an irreplaceable role in triggering the transition. This evidence implies that critical transition should be ascertained focusing the investigation at the system level (rather than investigating only molecular parameters) in a well-defined context, as the transition is strictly dependent on the microenvironment in which it occurs. Therefore, we need a systems biology approach to investigate EMT across the Waddington-like epigenetic landscape wherein the participation of both internal and external cues can be studied to follow the extent and the main characteristics of the phenotypic transition. Herein, we suggest a set of systems parameters (motility, invasiveness) altogether with specific molecular/histological markers to identify those critical observables, which can be integrated into a comprehensive mechanistic model.

PMID:38060188 | DOI:10.1007/978-1-0716-3577-3_13

Methods Mol Biol. 2024;2745:191-210. doi: 10.1007/978-1-0716-3577-3_12.

ABSTRACT

Inborn errors of metabolism (IEM) are a group of about 500 rare genetic diseases with large diversity and complexity due to number of metabolic pathways involved in. Establishing a correct diagnosis and identifying the specific clinical phenotype is consequently a difficult task. However, an inclusive diagnosis able in capturing the different clinical phenotypes is mandatory for successful treatment. However, in contrast with Garrod's basic assumption "one-gene one-disease," no "simple" correlation between genotype-phenotype can be vindicated in IEMs. An illustrative example of IEM is Phenylketonuria (PKU), an autosomal recessive inborn error of L-phenylalanine (Phe) metabolism, ascribed to variants of the phenylalanine hydroxylase (PAH) gene encoding for the enzyme complex phenylalanine-hydroxylase. Blood values of Phe allow classifying PKU into different clinical phenotypes, albeit the participation of other genetic/biochemical pathways in the pathogenetic mechanisms remains elusive. Indeed, it has been shown that the most serious complications, such as cognitive impairment, are not only related to the gene dysfunction but also to the patient's background and the participation of several nongenetic factors.Therefore, a Systems Biology-based strategy is required in addressing IEM complexity, and in identifying the interplay between different pathways in shaping the clinical phenotype. Such an approach should entail the concerted investigation of genomic, transcriptomics, proteomics, metabolomics profiles altogether with phenylalanine and amino acids metabolism. Noticeably, this "omic" perspective could be instrumental in planning personalized treatment, tailored accordingly to the disease profile and prognosis.

PMID:38060187 | DOI:10.1007/978-1-0716-3577-3_12

Methods Mol Biol. 2024;2745:177-188. doi: 10.1007/978-1-0716-3577-3_11.

ABSTRACT

Stromal-epithelial interactions mediate mammary gland development and the formation and progression of breast cancer. To study these interactions in vitro, 3D models are essential. We have successfully developed novel 3D in vitro models that allow the formation of mammary gland structures closely resembling those found in vivo and that respond to the hormonal cues that regulate mammary gland morphogenesis and function. Due to their simplicity when compared to in vivo studies, and to their accessibility to visualization in real time, these models are well suited to conceptual and mathematical modeling.

PMID:38060186 | DOI:10.1007/978-1-0716-3577-3_11

Methods Mol Biol. 2024;2745:121-134. doi: 10.1007/978-1-0716-3577-3_8.

ABSTRACT

Not unlike the climate or what holds the galaxies and planetary motions together, cancer biology has an intrinsic nonlinear dynamic. In this overview we will outline how to connect temporal measurements of a nonlinear dynamical and unstable complex system, such as cancer, with well-established engineering methods, old and new, that are applied in linear dynamical systems.This proof-of-concept is therapeutically relevant in the development of new means to treat or control human cancer by either adding an appropriate external "damping" or a "forcing" term, or by a "control" actuator such that its nonlinear dynamic is steered to a spiral stably into zero forever as a sink attractor.

PMID:38060183 | DOI:10.1007/978-1-0716-3577-3_8

Methods Mol Biol. 2024;2745:77-90. doi: 10.1007/978-1-0716-3577-3_5.

ABSTRACT

Metabolomics can provide diagnostic, prognostic, and therapeutic biomarker profiles of individual patients because a large number of metabolites can be simultaneously measured in biological samples in an unbiased manner. Minor stimuli can result in substantial alterations, making it a valuable target for analysis. Due to the complexity and sensitivity of the metabolome, studies must be devised to maintain consistency, minimize subject-to-subject variation, and maximize information recovery. This effort has been aided by technological advances in experimental design, rodent models, and instrumentation. Proton Nuclear Magnetic Resonance (1H-NMR) spectroscopy of biofluids, such as plasma, urine, and faeces provide the opportunity to identify biomarker change patterns that reflect the physiological or pathological status of an individual patient. Metabolomics has the ultimate potential to be useful in a clinical context, where it could be used to predict treatment response and survival and for early disease diagnosis. During drug treatment, an individual's metabolic status could be monitored and used to predict deleterious effects. Therefore, metabolomics has the potential to improve disease diagnosis, treatment, and follow-up care. In this chapter, we demonstrate how a metabolomics study can be used to diagnose a disease by classifying patients as either healthy or pathological, while accounting for individual variation.

PMID:38060180 | DOI:10.1007/978-1-0716-3577-3_5

Methods Mol Biol. 2024;2745:45-75. doi: 10.1007/978-1-0716-3577-3_4.

ABSTRACT

The thermodynamic formalism of nonequilibrium systems together with the theory of complex systems and systems biology offer an appropriate theoretical framework to explain the complexity observed at the macroscopic level in physiological phenomena. In turn, they allow the establishment of an appropriate conceptual and operational framework to address the study of phenomena such as the emergence and evolution of cancer.This chapter is organized as follows: In Subheading 1, an integrated vision of these disciplines is offered for the characterization of the emergence and evolution of cancer, seen as a nonlinear dynamic system, temporally and spatially self-organized out of thermodynamic equilibrium. The development of the various mathematical models and different techniques and approaches used in the characterization of cancer metastasis is presented in Subheading 2. Subheading 3 is devoted to the time course of cancer metastasis, with particular emphasis on the epithelial-mesenchymal transition (EMT henceforth) as well as chronotherapeutic treatments. In Subheading 4, models of the spatial evolution of cancer metastasis are presented. Finally, in Subheading 5, some conclusions and remarks are presented.

PMID:38060179 | DOI:10.1007/978-1-0716-3577-3_4

Methods Mol Biol. 2024;2745:3-19. doi: 10.1007/978-1-0716-3577-3_1.

ABSTRACT

Living cells display dynamic and complex behaviors. To understand their response and to infer novel insights not possible with traditional reductionist approaches, over the last few decades various computational modelling methodologies have been developed. In this chapter, we focus on modelling the dynamic metabolic response, using linear and nonlinear ordinary differential equations, of an engineered Escherichia coli MG1655 strain with plasmid pJBEI-6409 that produces limonene. We show the systems biology steps involved from collecting time-series data of living cells, to dynamic model creation and fitting the model with experimental responses using COPASI software.

PMID:38060176 | DOI:10.1007/978-1-0716-3577-3_1

Methods Mol Biol. 2024;2732:251-264. doi: 10.1007/978-1-0716-3515-5_17.

ABSTRACT

Nanopore sequencing has proven to be a useful tool for the generic detection of plant viruses, especially in laboratories working with small number of samples. In this chapter, we describe the steps prior to library preparation as well as the library preparation itself, which we found provides comparable results to Illumina sequencing.

PMID:38060130 | DOI:10.1007/978-1-0716-3515-5_17

Methods Mol Biol. 2024;2732:155-164. doi: 10.1007/978-1-0716-3515-5_11.

ABSTRACT

Metagenomics is vastly improving our ability to discover new viruses, as well as their possible associations with disease. However, metagenomics has also changed our understanding of viruses in general. This is because we can find viruses in healthy hosts in the absence of disease, which changes the perspective of viruses as mere pathogens and offers a new perspective in which viruses function as important components of ecosystems. In concrete, human blood metagenomics has revealed the presence of different types of viruses in apparently healthy subjects. These viruses are human anelloviruses and, to a lower extent, human pegiviruses. Viral metagenomics' major challenge is the correct isolation of the viral nucleic acids from a specific sample. For the protocol to be successful, all steps must be carefully chosen, in particular those that optimize the recovery of viral nucleic acids. Here, we present a procedure that allows the recovery of both DNA and RNA viruses from plasma samples.

PMID:38060124 | DOI:10.1007/978-1-0716-3515-5_11

Adv Sci (Weinh). 2023 Dec 7:e2302903. doi: 10.1002/advs.202302903. Online ahead of print.

ABSTRACT

The knowledge of the blood microvasculature and its functional role in health and disease has grown significantly attributable to decades of research and numerous advances in cell biology and tissue engineering; however, the lymphatics (the secondary vascular system) has not garnered similar attention, in part due to a lack of relevant in vitro models that mimic its pathophysiological functions. Here, a microfluidic-based approach is adopted to achieve precise control over the biological transport of growth factors and interstitial flow that drive the in vivo growth of lymphatic capillaries (lymphangiogenesis). The engineered on-chip lymphatics with in vivo-like morphology exhibit tissue-scale functionality with drainage rates of interstitial proteins and molecules comparable to in vivo standards. Computational and scaling analyses of the underlying transport phenomena elucidate the critical role of the three-dimensional geometry and lymphatic endothelium in recapitulating physiological drainage. Finally, the engineered on-chip lymphatics enabled studies of lymphatic-immune interactions that revealed inflammation-driven responses by the lymphatics to recruit immune cells via chemotactic signals similar to in vivo, pathological events. This on-chip lymphatics platform permits the interrogation of various lymphatic biological functions, as well as screening of lymphatic-based therapies such as interstitial absorption of protein therapeutics and lymphatic immunomodulation for cancer therapy.

PMID:38059806 | DOI:10.1002/advs.202302903

Gut Microbes. 2023 Dec;15(2):2290318. doi: 10.1080/19490976.2023.2290318. Epub 2023 Dec 7.

ABSTRACT

Iron is required for the replication and growth of almost all bacterial species and in the production of myelin and neurotransmitters. Increasing clinical studies evidence that the gut microbiota plays a critical role in iron metabolism and cognition. However, the understanding of the complex iron-microbiome-cognition crosstalk remains elusive. In a recent study in the Aging Imageomics cohort (n = 1,030), we identified a positive association of serum ferritin (SF) with executive function (EF) as inferred from the semantic verbal fluency (SVF,) the total digit span (TDS) and the phonemic verbal fluency tests (PVF). Here, we explored the potential mechanisms by analyzing the gut microbiome and plasma metabolome using shotgun metagenomics and HPLC-ESI-MS/MS, respectively. Different bacterial species belonging to the Proteobacteria phylum (Klebsiella pneumoniae, Klebsiella michiganensis, Unclassified Escherichia) were negatively associated both with SF and executive function. At the functional level, an enrichment of microbial pathways involved in phenylalanine, arginine, and proline metabolism was identified. Consistently, phenylacetylglutamine, a metabolite derived from microbial catabolism of phenylalanine, was negatively associated with SF, EF, and semantic memory. Other metabolites such as ureidobutyric acid and 19,20-DiHDPA, a DHA-derived oxylipin, were also consistently and negatively associated with SF, EF, and semantic memory, while plasma eicosapentaenoic acid was positively associated. The associations of SF with cognition could be mediated by the gut microbiome through microbial-derived metabolites.

PMID:38059755 | DOI:10.1080/19490976.2023.2290318

Gut Microbes. 2023 Dec;15(2):2286675. doi: 10.1080/19490976.2023.2286675. Epub 2023 Dec 7.

ABSTRACT

Inflammatory bowel disease (IBD) is a persistent inflammatory condition that affects the gastrointestinal tract and presents significant challenges in its management and treatment. Despite the knowledge that within-host bacterial evolution occurs in the intestine, the disease has rarely been studied from an evolutionary perspective. In this study, we aimed to investigate the evolution of resident bacteria during intestinal inflammation and whether- and how disease-related bacterial genetic changes may present trade-offs with potential therapeutic importance. Here, we perform an in vivo evolution experiment of E. coli in a gnotobiotic mouse model of IBD, followed by multiomic analyses to identify disease-specific genetic and phenotypic changes in bacteria that evolved in an inflamed versus a non-inflamed control environment. Our results demonstrate distinct evolutionary changes in E. coli specific to inflammation, including a single nucleotide variant that independently reached high frequency in all inflamed mice. Using ex vivo fitness assays, we find that these changes are associated with a higher fitness in an inflamed environment compared to isolates derived from non-inflamed mice. Further, using large-scale phenotypic assays, we show that bacterial adaptation to inflammation results in clinically relevant phenotypes, which intriguingly include collateral sensitivity to antibiotics. Bacterial evolution in an inflamed gut yields specific genetic and phenotypic signatures. These results may serve as a basis for developing novel evolution-informed treatment approaches for patients with intestinal inflammation.

PMID:38059748 | DOI:10.1080/19490976.2023.2286675

Respir Res. 2023 Dec 6;24(1):305. doi: 10.1186/s12931-023-02620-1.

ABSTRACT

INTRODUCTION: Biomarkers are needed to inform the choice of biologic therapy in patients with asthma given the increasing number of biologics. We aimed to identify proteins associated with response to omalizumab and mepolizumab.

METHODS: Aptamer-based proteomic profiling (SomaScan) was used to assess 1437 proteins from 51 patients with moderate to severe asthma who received omalizumab (n = 29) or mepolizumab (n = 22). Response was defined as the change in asthma-related exacerbations in the 12 months following therapy initiation. All models were adjusted for age, sex, and pre-treatment exacerbation rate. Additionally, body mass index was included in the omalizumab model and eosinophil count in the mepolizumab model. We evaluated the association between molecular signatures and response using negative binomial regression correcting for the false discovery rate (FDR) and gene set enrichment analyses (GSEA) to identify associated pathways.

RESULTS: Over two-thirds of patients were female. The average age for omalizumab patients was 42 years and 57 years for mepolizumab. At baseline, the average exacerbation rate was 1.5/year for omalizumab and 2.4/year for mepolizumab. Lower levels of LOXL2 (unadjusted p: 1.93 × 10E-05, FDR-corrected: 0.028) and myostatin (unadjusted: 3.87 × 10E-05, FDR-corrected: 0.028) were associated with better response to mepolizumab. Higher levels of CD9 antigen (unadjusted: 5.30 × 10E-07, FDR-corrected: 0.0006) and MUC1 (unadjusted: 1.15 × 10E-06, FDR-corrected: 0.0006) were associated with better response to omalizumab, and LTB4R (unadjusted: 1.12 × 10E-06, FDR-corrected: 0.0006) with worse response. Protein-protein interaction network modeling showed an enrichment of the TNF- and NF-kB signaling pathways for patients treated with mepolizumab and multiple pathways involving MAPK, including the FcER1 pathway, for patients treated with omalizumab.

CONCLUSIONS: This study provides novel fundamental data on proteins associated with response to mepolizumab or omalizumab in severe asthma and warrants further validation as potential biomarkers for therapy selection.

PMID:38057814 | DOI:10.1186/s12931-023-02620-1

BMC Genomics. 2023 Dec 6;24(1):748. doi: 10.1186/s12864-023-09823-2.

ABSTRACT

BACKGROUND: Infection by beet cyst nematodes (BCN, Heterodera schachtii) causes a serious disease of sugar beet, and climatic change is expected to improve the conditions for BCN infection. Yield and yield stability under adverse conditions are among the main breeding objectives. Breeding of BCN tolerant sugar beet cultivars offering high yield in the presence of the pathogen is therefore of high relevance.

RESULTS: To identify causal genes providing tolerance against BCN infection, we combined several experimental and bioinformatic approaches. Relevant genomic regions were detected through mapping-by-sequencing using a segregating F2 population. DNA sequencing of contrasting F2 pools and analyses of allele frequencies for variant positions identified a single genomic region which confers nematode tolerance. The genomic interval was confirmed and narrowed down by genotyping with newly developed molecular markers. To pinpoint the causal genes within the potential nematode tolerance locus, we generated long read-based genome sequence assemblies of the tolerant parental breeding line Strube U2Bv and the susceptible reference line 2320Bv. We analyzed continuous sequences of the potential locus with regard to functional gene annotation and differential gene expression upon BCN infection. A cluster of genes with similarity to the Arabidopsis thaliana gene encoding nodule inception protein-like protein 7 (NLP7) was identified. Gene expression analyses confirmed transcriptional activity and revealed clear differences between susceptible and tolerant genotypes.

CONCLUSIONS: Our findings provide new insights into the genomic basis of plant-nematode interactions that can be used to design and accelerate novel management strategies against BCN.

PMID:38057719 | DOI:10.1186/s12864-023-09823-2