Mol Genet Metab Rep. 2023 May 15;35:100974. doi: 10.1016/j.ymgmr.2023.100974. eCollection 2023 Jun.

ABSTRACT

Metachromatic leukodystrophy (MLD) is a rare, autosomal recessive lysosomal storage disease. Deficient activity of arylsulfatase A causes sulfatides to accumulate in cells of different tissues, including those in the central and peripheral nervous systems, leading to progressive demyelination and neurodegeneration. Although there is some association between specific arylsulfatase A alleles and disease severity, genotype-phenotype correlations are not fully understood. We aimed to identify biomarker candidates of early tissue damage in MLD using a modeling approach based on systems biology. A review of the literature was performed in an initial disease characterization step, allowing identification of pathophysiological processes involved in MLD and proteins relating to these processes. Three mathematical models were generated to simulate different stages of MLD at the molecular level: an early pro-inflammatory stage model (including only processes considered to be active in the early stages of disease), a pre-demyelination stage model (including additional processes that are active after some disease progression), and a demyelination stage model (in which all pathophysiological processes are active). The models evaluated 3457 proteins of interest, individually and by pairs through data mining techniques, applying five filters to prioritize biomarkers that could differentiate between the models. Sixteen potential biomarkers were identified, including effectors relating to mitochondrial dysfunction, remyelination, and neurodegeneration. The findings were corroborated in a gene expression data set from T lymphocytes of patients with MLD; all candidates formed combinations that were able to distinguish patients with MLD from controls, and all but one candidate distinguished late-infantile MLD from juvenile MLD as part of a combinatorial biomarker pair. In particular, pro-neuregulin-1 appeared as differential on all comparisons (patients with MLD vs controls and within clinical subtypes); casein kinase II subunit alpha was detected as a potential individual marker within clinical subtypes. These findings provide a panel of biomarker candidates suitable for experimental validation and highlight the utility of mathematical models to identify biomarker candidates of early tissue damage in MLD with a high degree of accuracy and sensitivity.

PMID:37275681 | PMC:PMC10233284 | DOI:10.1016/j.ymgmr.2023.100974

Front Plant Sci. 2023 May 18;14:1167221. doi: 10.3389/fpls.2023.1167221. eCollection 2023.

ABSTRACT

Historically, end-product quality testing has been costly and required large flour samples; therefore, it was generally implemented in the late phases of variety development, imposing a huge cost on the breeding effort and effectiveness. High genetic correlations of end-product quality traits with higher throughput and nondestructive testing technologies, such as near-infrared (NIR), could enable early-stage testing and effective selection of these highly valuable traits in a multi-trait genomic prediction model. We studied the impact on prediction accuracy in genomic best linear unbiased prediction (GBLUP) of adding NIR-predicted secondary traits for six end-product quality traits (crumb yellowness, water absorption, texture hardness, flour yield, grain protein, flour swelling volume). Bread wheat lines (1,400-1,900) were measured across 8 years (2012-2019) for six end-product quality traits with standard laboratory assays and with NIR, which were combined to generate predicted data for approximately 27,000 lines. All lines were genotyped with the Infinium™ Wheat Barley 40K BeadChip and imputed using exome sequence data. End-product and NIR phenotypes were genetically correlated (0.5-0.83, except for flour swelling volume 0.19). Prediction accuracies of end-product traits ranged between 0.28 and 0.64 and increased by 30% through the inclusion of NIR-predicted data compared to single-trait analysis. There was a high correlation between the multi-trait prediction accuracy and genetic correlations between end-product and NIR-predicted data (0.69-0.77). Our forward prediction validation revealed a gradual increase in prediction accuracy when adding more years to the multi-trait model. Overall, we achieved genomic prediction accuracy at a level that enables selection for end-product quality traits early in the breeding cycle.

PMID:37275257 | PMC:PMC10233148 | DOI:10.3389/fpls.2023.1167221

Front Microbiol. 2023 May 18;14:1131953. doi: 10.3389/fmicb.2023.1131953. eCollection 2023.

ABSTRACT

Antibiotic exposure disturbs the developing infant gut microbiota. The capacity of the gut microbiota to recover from this disturbance (resilience) depends on the type of antibiotic. In this study, infant gut microbiota was exposed to a combination of amoxicillin and clavulanate (amoxicillin/clavulanate) in an in vitro colon model (TIM-2) with fecal-derived microbiota from 1-month-old (1-M; a mixed-taxa community type) as well as 3-month-old (3-M; Bifidobacterium dominated community type) breastfed infants. We investigated the effect of two common infant prebiotics, 2'-fucosyllactose (2'-FL) or galacto-oligosaccharides (GOS), on the resilience of infant gut microbiota to amoxicillin/clavulanate-induced changes in microbiota composition and activity. Amoxicillin/clavulanate treatment decreased alpha diversity and induced a temporary shift of microbiota to a community dominated by enterobacteria. Moreover, antibiotic treatment increased succinate and lactate in both 1- and 3-M colon models, while decreasing the production of short-chain (SCFA) and branched-chain fatty acids (BFCA). The prebiotic effect on the microbiota recovery depended on the fermenting capacity of antibiotic-exposed microbiota. In the 1-M colon model, the supplementation of 2'-FL supported the recovery of microbiota and restored the production of propionate and butyrate. In the 3-M colon model, GOS supplementation supported the recovery of microbiota and increased the production of acetate and butyrate.

PMID:37275167 | PMC:PMC10232780 | DOI:10.3389/fmicb.2023.1131953

Front Genet. 2023 May 18;14:1084482. doi: 10.3389/fgene.2023.1084482. eCollection 2023.

ABSTRACT

Identification of long non-coding RNAs (lncRNAs) associated with common diseases is crucial for patient self-diagnosis and monitoring of health conditions using artificial intelligence (AI) technology at home. LncRNAs have gained significant attention due to their crucial roles in the pathogenesis of complex human diseases and identifying their associations with diseases can aid in developing diagnostic biomarkers at the molecular level. Computational methods for predicting lncRNA-disease associations (LDAs) have become necessary due to the time-consuming and labor-intensive nature of wet biological experiments in hospitals, enabling patients to access LDAs through their AI terminal devices at any time. Here, we have developed a predictive tool, LDAGRL, for identifying potential LDAs using a bridge heterogeneous information network (BHnet) constructed via Structural Deep Network Embedding (SDNE). The BHnet consists of three types of molecules as bridge nodes to implicitly link the lncRNA with disease nodes and the SDNE is used to learn high-quality node representations and make LDA predictions in a unified graph space. To assess the feasibility and performance of LDAGRL, extensive experiments, including 5-fold cross-validation, comparison with state-of-the-art methods, comparison on different classifiers and comparison of different node feature combinations, were conducted, and the results showed that LDAGRL achieved satisfactory prediction performance, indicating its potential as an effective LDAs prediction tool for family medicine and primary care.

PMID:37274787 | PMC:PMC10234424 | DOI:10.3389/fgene.2023.1084482

Front Genet. 2023 May 18;14:1215987. doi: 10.3389/fgene.2023.1215987. eCollection 2023.

NO ABSTRACT

PMID:37274783 | PMC:PMC10233740 | DOI:10.3389/fgene.2023.1215987

Mol Syst Des Eng. 2022 Aug 1;7(8):915-932. doi: 10.1039/d2me00002d. Epub 2022 May 6.

ABSTRACT

Labeled protein-based biomaterials have become a popular for various biomedical applications such as tissue-engineered, therapeutic, or diagnostic scaffolds. Labeling of protein biomaterials, including with ultrasmall super-paramagnetic iron oxide (USPIO) nanoparticles, has enabled a wide variety of imaging techniques. These USPIO-based biomaterials are widely studied in magnetic resonance imaging (MRI), thermotherapy, and magnetically-driven drug delivery which provide a method for direct and non-invasive monitoring of implants or drug delivery agents. Where most developments have been made using polymers or collagen hydrogels, shown here is the use of a rationally designed protein as the building block for a meso-scale fiber. While USPIOs have been chemically conjugated to antibodies, glycoproteins, and tissue-engineered scaffolds for targeting or improved biocompatibility and stability, these constructs have predominantly served as diagnostic agents and often involve harsh conditions for USPIO synthesis. Here, we present an engineered protein-iron oxide hybrid material comprised of an azide-functionalized coiled-coil protein with small molecule binding capacity conjugated via bioorthogonal azide-alkyne cycloaddition to an alkyne-bearing iron oxide templating peptide, CMms6, for USPIO biomineralization under mild conditions. The coiled-coil protein, dubbed Q, has been previously shown to form nanofibers and, upon small molecule binding, further assembles into mesofibers via encapsulation and aggregation. The resulting hybrid material is capable of doxorubicin encapsulation as well as sensitive T2*-weighted MRI darkening for strong imaging capability that is uniquely derived from a coiled-coil protein.

PMID:37274761 | PMC:PMC10237276 | DOI:10.1039/d2me00002d

mSystems. 2023 Jun 5:e0000423. doi: 10.1128/msystems.00004-23. Online ahead of print.

ABSTRACT

The soil bacterium Pseudomonas putida is a robust biomanufacturing host that assimilates a broad range of substrates while efficiently coping with adverse environmental conditions. P. putida is equipped with functions related to one-carbon (C1) compounds (e.g. methanol, formaldehyde, and formate) oxidation-yet pathways to assimilate these carbon sources are largely absent. In this work, we adopted a systems-level approach to study the genetic and molecular basis of C1 metabolism in P. putida. RNA sequencing identified two oxidoreductases, encoded by PP_0256 and PP_4596, transcriptionally active in the presence of formate. Quantitative physiology of deletion mutants revealed growth defects at high formate concentrations, pointing to an important role of these oxidoreductases in C1 tolerance. Moreover, we describe a concerted detoxification process for methanol and formaldehyde, the C1 intermediates upstream formate. Alcohol oxidation to highly-reactive formaldehyde by PedEH and other broad-substrate-range dehydrogenases underpinned the (apparent) suboptimal methanol tolerance of P. putida. Formaldehyde was mostly processed by a glutathione-dependent mechanism encoded in the frmAC operon, and thiol-independent FdhAB and AldB-II overtook detoxification at high aldehyde concentrations. Deletion strains were constructed and characterized towards unveiling these biochemical mechanisms, underscoring the worth of P. putida for emergent biotechnological applications-e.g. engineering synthetic formatotrophy and methylotrophy.IMPORTANCEC1 substrates continue to attract interest in biotechnology, as their use is both cost-effective and ultimately expected to mitigate the impact of greenhouse gas emissions. However, our current understanding of bacterial C1 metabolism remains relatively limited in species that cannot grow on (i.e., assimilate) these substrates. Pseudomonas putida, a model Gram-negative environmental bacterium, constitutes a prime example of this sort. The biochemical pathways active in response to methanol, formaldehyde, and formate have been largely overlooked-although the ability of P. putida to process C1 molecules has been previously alluded to in the literature. By using a systems-level strategy, this study bridges such knowledge gap through the identification and characterization of mechanisms underlying methanol, formaldehyde, and formate detoxification-including hitherto unknown enzymes that act on these substrates. The results reported herein both expand our understanding of microbial metabolism and lay a solid foundation for engineering efforts toward valorizing C1 feedstocks.

PMID:37273222 | DOI:10.1128/msystems.00004-23

Microb Genom. 2023 Jun;9(6). doi: 10.1099/mgen.0.001032.

ABSTRACT

Carbapenem-resistant Klebsiella pneumoniae is a major cause of hospital-acquired infections and the fastest-growing pathogen in Europe. Carbapenem resistance was detected at the Consorcio Hospital General Universitario de Valencia (CHGUV) in early 2015, and there has been a significant increase in carbapenem-resistant isolates since then. In this study, we collected carbapenem-resistant isolates from this hospital during the period of increase (from 2015 to 2019) and studied how K. pneumoniae carbapenem-resistant isolates emerged and spread in the hospital. A total of 225 isolates were subjected to whole-genome sequencing with Illumina NextSeq. We characterized the isolates by identifying lineages and antimicrobial resistance genes and plasmids, especially those related to reduced carbapenem susceptibility. Our findings show that the initial carbapenem resistance emergence and dissemination at the CHGUV occurred during a short period of 1 year. Furthermore, it was complex, involving six different lineages of types ST307, ST11, ST101 and ST437, different resistance-determinant factors, including OXA-48, NDM-1, NDM-23 and DHA-1, and different plasmids.

PMID:37272914 | DOI:10.1099/mgen.0.001032

Microbiol Spectr. 2023 Jun 5:e0485122. doi: 10.1128/spectrum.04851-22. Online ahead of print.

ABSTRACT

Vibrio parahaemolyticus is a bacterial pathogen that becomes lethal to Penaeus shrimps when acquiring the pVA1-type plasmid carrying the PirABvp genes, causing acute hepatopancreatic necrosis disease (AHPND). This disease causes significant losses across the world, with outbreaks reported in Southeast Asia, Mexico, and South America. Virulence level and mortality differences have been reported in isolates from different locations, and whether this phenomenon is caused by plasmid-related elements or genomic-related elements from the bacteria remains unclear. Here, nine genomes of South American AHPND-causing V. parahaemolyticus (VPAHPND) isolates were assembled and analyzed using a comparative genomics approach at (i) whole-genome, (ii) secretion system, and (iii) plasmid level, and then included for a phylogenomic analysis with another 86 strains. Two main results were obtained from our analyses. First, all isolates contained pVA1-type plasmids harboring the toxin coding genes, and with high similarity with the prototypical sequence of Mexican-like origin, while phylogenomic analysis showed some level of heterogeneity with discrete clusters and wide diversity compared to other available genomes. Second, although a high genomic similarity was observed, variation in virulence genes and clusters was observed, which might be relevant in the expression of the disease. Overall, our results suggest that South American pathogenic isolates are derived from various genetic lineages which appear to have acquired the plasmid through horizontal gene transfer. Furthermore, pathogenicity seems to be a multifactorial trait where the degree of virulence could be altered by the presence or variations of several virulence factors. IMPORTANCE AHPND have caused losses of over $2.6 billion to the aquaculture industry around the world due to its high mortality rate in shrimp farming. The most common etiological agent is V. parahaemolyticus strains possessing the pVA1-type plasmid carrying the PirABvp toxin. Nevertheless, complete understanding of the role of genetic elements and their impact in the virulence of this pathogen remains unclear. In this work, we analyzed nine South American AHPND-causing V. parahaemolyticus isolates at a genomic level, and assessed their evolutionary relationship with other 86 strains. We found that all our isolates were highly similar and possessed the Mexican-type plasmid, but their genomic content did not cluster with other Mexican strains, but instead were spread across all isolates. These results suggest that South American VPAHPND have different genetic backgrounds, and probably proceed from diverse geographical locations, and acquire the pVA1-type plasmid via horizontal gene transfer at different times.

PMID:37272817 | DOI:10.1128/spectrum.04851-22

Appl Environ Microbiol. 2023 Jun 5:e0050023. doi: 10.1128/aem.00500-23. Online ahead of print.

ABSTRACT

Microbial assembly and metabolic potential in the subsurface critical zone (SCZ) are substantially impacted by subsurface geochemistry and hydrogeology, selecting for microbes distinct from those in surficial soils. In this study, we integrated metagenomics and geochemistry to elucidate how microbial composition and metabolic potential are shaped and impacted by vertical variations in geochemistry and hydrogeology in terrestrial subsurface sediment. A sediment core from an uncontaminated, pristine well at Oak Ridge Field Research Center in Oak Ridge, Tennessee, including the shallow subsurface, vadose zone, capillary fringe, and saturated zone, was used in this study. Our results showed that subsurface microbes were highly localized and that communities were rarely interconnected. Microbial community composition as well as metabolic potential in carbon and nitrogen cycling varied even over short vertical distances. Further analyses indicated a strong depth-related covariation of community composition with a subset of 12 environmental variables. An analysis of dissolved organic carbon (DOC) quality via ultrahigh resolution mass spectrometry suggested that the SCZ was generally a low-carbon environment, with the relative portion of labile DOC decreasing and that of recalcitrant DOC increasing along the depth, selecting microbes from copiotrophs to oligotrophs and also impacting the microbial metabolic potential in the carbon cycle. Our study demonstrates that sediment geochemistry and hydrogeology are vital in the selection of distinct microbial populations and metabolism in the SCZ. IMPORTANCE In this study, we explored the links between geochemical parameters, microbial community structure and metabolic potential across the depth of sediment, including the shallow subsurface, vadose zone, capillary fringe, and saturated zone. Our results revealed that microbes in the terrestrial subsurface can be highly localized, with communities rarely being interconnected along the depth. Overall, our research demonstrates that sediment geochemistry and hydrogeology are vital in the selection of distinct microbial populations and metabolic potential in different depths of subsurface terrestrial sediment. Such studies correlating microbial community analyses and geochemistry analyses, including high resolution mass spectrometry analyses of natural organic carbon, will further the fundamental understanding of microbial ecology and biogeochemistry in subsurface terrestrial ecosystems and will benefit the future development of predictive models on nutrient turnover in these environments.

PMID:37272792 | DOI:10.1128/aem.00500-23

Plant Commun. 2023 Jun 3:100633. doi: 10.1016/j.xplc.2023.100633. Online ahead of print.

ABSTRACT

JUJUNCAO (Cenchrus fungigraminus; 2n=4x=28) is a Cenchrus grass with the highest productive biomass among cultivated plants, and could be used for the cultivation of mushrooms, animal feed and biofuel production. Here, we reported a near completely assembled genome of JUJUNCAO and discovered that JUJUNCAO was an allopolyploid originated ∼2.7 MYA. Its genome consisted of two subgenomes, with subgenome A sharing a high collinear synteny with pearl millet. We also investigated the genome evolution of JUJUNCAO and suggested that the ancestral karyotype of Cenchrus split into the A and B ancestral karyotypes of JUJUNCAO. Comparative transcriptome and DNA methylome analyses revealed a functional divergence of the homeologous gene pairs between the two subgenomes, which was a further indication of asymmetric DNA methylation. The three types of centromeric repeats in the JUJUNCAO genome (CEN137, CEN148 and CEN156) may have evolved independently within each subgenome, with some introgressions of CEN156 from B subgenome into A subgenome. We further investigated the photosynthetic characteristics of JUJUNCAO which revealed a typical C4 Kranz anatomy and a high photosynthetic efficiency. Moreover, NADP-ME and PEPCK in JUJUNCAO very likely have co-operated in the major C4 decarboxylation reaction, which is different from other C4 photosynthetic subtypes reported and may contribute to the high photosynthetic efficiency and consequently high biomass yield of JUJUNCAO. Taken together, our results provide insights into the highly efficient photosynthetic mechanism in JUJUNCAO and are a valuable reference genome for future genetic and evolutionary studies, as well as the genetic improvement of the Cenchrus grasses.

PMID:37271992 | DOI:10.1016/j.xplc.2023.100633

Phytomedicine. 2023 May 24;116:154902. doi: 10.1016/j.phymed.2023.154902. Online ahead of print.

ABSTRACT

BACKGROUND: Gastric cancer (GC) is a common malignant tumor with limited treatment options. The natural flavonoid nobiletin (NOB) is a beneficial antioxidant that possesses anticancer activity. However, the mechanisms by which NOB inhibits GC progression remain unclear.

METHODS: A CCK-8 assay was performed to determine cytotoxicity. Cell cycle and apoptosis analyses were performed by flow cytometry. RNA-seq was performed to detect differential gene expression after NOB treatment. RT‒qPCR, Western blot and immunofluorescence staining were used to examine the underlying mechanisms of NOB in GC. Xenograft tumor models were constructed to verify the effect of NOB and its specific biological mechanism in GC.

RESULTS: NOB inhibited cell proliferation, caused cell cycle arrest and induced apoptosis in GC cells. KEGG classification identified that the inhibitory effect of NOB on GC cells mainly involved the lipid metabolism pathway. We further showed that NOB reduced de novo fatty acid (FA) synthesis, as evidenced by the decreased levels of neutral lipids and the expression levels of ACLY, ACACA and FASN, and ACLY abrogated the effect of NOB on lipid deposits in GC cells. In addition, we also found that NOB triggered endoplasmic reticulum (ER) stress by activating the IRE-1α/GRP78/CHOP axis, but overexpression of ACLY reversed ER stress. Mechanistically, inhibiting ACLY expression with NOB significantly reduced neutral lipid accumulation, thereby inducing apoptosis by activating IRE-1α-mediated ER stress and inhibiting GC cell progression. Finally, in vivo results also demonstrated that NOB inhibited tumor growth by decreasing de novo FA synthesis.

CONCLUSION: NOB could inhibit the expression of ACLY to activate IRE-1α-induced ER stress, which ultimately led to GC cell apoptosis. Our results provide novel insight into the use of de novo FA synthesis for GC treatment and are the first to reveal that NOB inhibits GC progression by ACLY-dependent ER stress.

PMID:37270969 | DOI:10.1016/j.phymed.2023.154902

NPJ Syst Biol Appl. 2023 Jun 3;9(1):22. doi: 10.1038/s41540-023-00283-8.

ABSTRACT

Pancreatic neuroendocrine tumors (PanNETs) are a rare tumor entity with largely unpredictable progression and increasing incidence in developed countries. Molecular pathways involved in PanNETs development are still not elucidated, and specific biomarkers are missing. Moreover, the heterogeneity of PanNETs makes their treatment challenging and most approved targeted therapeutic options for PanNETs lack objective responses. Here, we applied a systems biology approach integrating dynamic modeling strategies, foreign classifier tailored approaches, and patient expression profiles to predict PanNETs progression as well as resistance mechanisms to clinically approved treatments such as the mammalian target of rapamycin complex 1 (mTORC1) inhibitors. We set up a model able to represent frequently reported PanNETs drivers in patient cohorts, such as Menin-1 (MEN1), Death domain associated protein (DAXX), Tuberous Sclerosis (TSC), as well as wild-type tumors. Model-based simulations suggested drivers of cancer progression as both first and second hits after MEN1 loss. In addition, we could predict the benefit of mTORC1 inhibitors on differentially mutated cohorts and hypothesize resistance mechanisms. Our approach sheds light on a more personalized prediction and treatment of PanNET mutant phenotypes.

PMID:37270586 | DOI:10.1038/s41540-023-00283-8

BMC Infect Dis. 2023 Jun 3;23(1):373. doi: 10.1186/s12879-023-08348-z.

ABSTRACT

BACKGROUND: Individuals in close contact with active pulmonary tuberculosis (TB) patients showed a high risk of recent infection and, once infected, higher risk of developing active TB in the following years post-exposure. But the peak time of active disease onset is unclear. This study aims to estimate post exposure TB incidence risk among close contacts to provide reference for clinical and public health strategies.

METHODS: We searched PubMed, Web of Science, and EMBASE for articles published until December 1, 2022. The incidence rates were quantitatively summarized by means of meta-analysis using the random-effect model.

RESULTS: Of the 5616 studies, 31 studies included in our analysis. For baseline close contacts results, the summarized prevalence of Mycobacterium tuberculosis (MTB) infection and active TB was found to be 46.30% (95% CI: 37.18%-55.41%) and 2.68% (95% CI: 2.02%-3.35%), respectively. During the follow-up, the 1-year, 2-year and 5-year cumulative incidence of TB in close contacts were 2.15% (95% CI: 1.51%-2.80%), 1.21% (95% CI: 0.93%-1.49%) and 1.11% (95% CI: 0.64%-1.58%), respectively. Individuals with a positive result of MTB infection testing at baseline showed significantly higher cumulative TB incidence as compared to those negatives (3.80% vs. 0.82%, p < 0.001).

CONCLUSIONS: Individuals with close contact to active pulmonary TB patients are bearing significant risk of developing active TB, particularly within the first-year post-exposure. Population with recent infections should be an important priority for active case finding and preventive intervention worldwide.

PMID:37270474 | DOI:10.1186/s12879-023-08348-z

Cell. 2023 May 26:S0092-8674(23)00476-2. doi: 10.1016/j.cell.2023.05.002. Online ahead of print.

ABSTRACT

Lifespan varies within and across species, but the general principles of its control remain unclear. Here, we conducted multi-tissue RNA-seq analyses across 41 mammalian species, identifying longevity signatures and examining their relationship with transcriptomic biomarkers of aging and established lifespan-extending interventions. An integrative analysis uncovered shared longevity mechanisms within and across species, including downregulated Igf1 and upregulated mitochondrial translation genes, and unique features, such as distinct regulation of the innate immune response and cellular respiration. Signatures of long-lived species were positively correlated with age-related changes and enriched for evolutionarily ancient essential genes, involved in proteolysis and PI3K-Akt signaling. Conversely, lifespan-extending interventions counteracted aging patterns and affected younger, mutable genes enriched for energy metabolism. The identified biomarkers revealed longevity interventions, including KU0063794, which extended mouse lifespan and healthspan. Overall, this study uncovers universal and distinct strategies of lifespan regulation within and across species and provides tools for discovering longevity interventions.

PMID:37269831 | DOI:10.1016/j.cell.2023.05.002

Proteomics. 2023 Jun 3:e2200407. doi: 10.1002/pmic.202200407. Online ahead of print.

ABSTRACT

Multiomics approaches to studying systems biology are very powerful techniques that can elucidate changes in the genomic, transcriptomic, proteomic, and metabolomic levels within a cell type in response to an infection. These approaches are valuable for understanding the mechanisms behind disease pathogenesis and how the immune system responds to being challenged. With the emergence of the COVID-19 pandemic, the importance and utility of these tools have become evident in garnering a better understanding of the systems biology within the innate and adaptive immune response and for developing treatments and preventative measures for new and emerging pathogens that pose a threat to human health. In this review, we focus on state-of-the-art omics technologies within the scope of innate immunity.

PMID:37269203 | DOI:10.1002/pmic.202200407

Adv Sci (Weinh). 2023 Jun 2:e2207322. doi: 10.1002/advs.202207322. Online ahead of print.

ABSTRACT

Accumulated genetic alterations in cancer cells distort cellular stimulus-response (or input-output) relationships, resulting in uncontrolled proliferation. However, the complex molecular interaction network within a cell implicates a possibility of restoring such distorted input-output relationships by rewiring the signal flow through controlling hidden molecular switches. Here, a system framework of analyzing cellular input-output relationships in consideration of various genetic alterations and identifying possible molecular switches that can normalize the distorted relationships based on Boolean network modeling and dynamics analysis is presented. Such reversion is demonstrated by the analysis of a number of cancer molecular networks together with a focused case study on bladder cancer with in vitro experiments and patient survival data analysis. The origin of reversibility from an evolutionary point of view based on the redundancy and robustness intrinsically embedded in complex molecular regulatory networks is further discussed.

PMID:37269056 | DOI:10.1002/advs.202207322

Nat Commun. 2023 Jun 2;14(1):2947. doi: 10.1038/s41467-023-37689-1.

ABSTRACT

Derangements of the blood-brain barrier (BBB) or blood-retinal barrier (BRB) occur in disorders ranging from stroke, cancer, diabetic retinopathy, and Alzheimer's disease. The Norrin/FZD4/TSPAN12 pathway activates WNT/β-catenin signaling, which is essential for BBB and BRB function. However, systemic pharmacologic FZD4 stimulation is hindered by obligate palmitoylation and insolubility of native WNTs and suboptimal properties of the FZD4-selective ligand Norrin. Here, we develop L6-F4-2, a non-lipidated, FZD4-specific surrogate which significantly improves subpicomolar affinity versus native Norrin. In Norrin knockout (NdpKO) mice, L6-F4-2 not only potently reverses neonatal retinal angiogenesis deficits, but also restores BRB and BBB function. In adult C57Bl/6J mice, post-stroke systemic delivery of L6-F4-2 strongly reduces BBB permeability, infarction, and edema, while improving neurologic score and capillary pericyte coverage. Our findings reveal systemic efficacy of a bioengineered FZD4-selective WNT surrogate during ischemic BBB dysfunction, with potential applicability to adult CNS disorders characterized by an aberrant blood-brain barrier.

PMID:37268690 | DOI:10.1038/s41467-023-37689-1

J Dairy Sci. 2023 May 31:S0022-0302(23)00311-9. doi: 10.3168/jds.2022-23082. Online ahead of print.

ABSTRACT

Selection of competent recipients before embryo transfer (ET) is indispensable for improving pregnancy and birth rates in cattle. However, pregnancy prediction can fail when the competence of the embryo is ignored. We hypothesized that the pregnancy potential of biomarkers could improve with information on embryonic competence. In vitro produced (IVP) embryos cultured singly for 24 h (from d 6 to 7) were transferred to d 7 synchronized recipients as fresh or after freezing and thawing. Recipient blood was collected on d 0 (estrus; n = 108) and d 7 (4-6 h before ET; n = 107) and plasma was analyzed by nuclear magnetic resonance (1H+NMR). Spent embryo culture medium (CM) was collected and analyzed by UHPLC-MS/MS in a subset of n = 70 samples. Concentrations of metabolites quantified in plasma (n = 35) were statistically analyzed as a function of pregnancy diagnosed on d 40, d 62 and birth. Univariate analysis with plasma metabolites consisted of a block study with controllable fixed factors (i.e., embryo cryopreservation, recipient breed, and day of blood collection; Wilcoxon test and t-test). Metabolite concentrations in recipients and embryos were independently analyzed by iterations that reclassified embryos or recipients using the support vector machine (SVM). Iterations identified some competent embryos, but mostly competent recipients that had a pregnancy incompetent partner embryo. Misclassified recipients that could be classified as competent were reanalyzed in a new iteration to improve the predictive model. After subsequent iterations, the predictive potential of recipient biomarkers was recalculated. On d 0, creatine, acetone and l-phenylalanine were the most relevant biomarkers at d 40, d 62, and birth, and on d 7, l-glutamine, l-lysine, and ornithine. Creatine was the most representative biomarker within blocks (n = 20), with a uniform distribution over pregnancy endpoints and type of embryos. Biomarkers showed higher abundance on d 7 than d 0, were more predictive for d 40 and d 62 than at birth, and the pregnancy predictive ability was lower with frozen-thawed (F-T) embryos. Six metabolic pathways differed between d 40 pregnant recipients for fresh and F-T embryos. Within F-T embryos, more recipients were misclassified, probably due to pregnancy losses, but were accurately identified when combined with embryonic metabolite signals. After recalculation, 12 biomarkers increased ROC-AUC (>0.65) at birth, highlighting creatine (ROC-AUC = 0.851), and 5 new biomarkers were identified. Combining metabolic information of recipient and embryos improves the confidence and accuracy of single biomarkers.

PMID:37268566 | DOI:10.3168/jds.2022-23082

Thorax. 2023 Jun 2:thoraxjnl-2022-219158. doi: 10.1136/thorax-2022-219158. Online ahead of print.

ABSTRACT

BACKGROUND: Treatment and preventative advances for chronic obstructive pulmonary disease (COPD) have been slow due, in part, to limited subphenotypes. We tested if unsupervised machine learning on CT images would discover CT emphysema subtypes with distinct characteristics, prognoses and genetic associations.

METHODS: New CT emphysema subtypes were identified by unsupervised machine learning on only the texture and location of emphysematous regions on CT scans from 2853 participants in the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS), a COPD case-control study, followed by data reduction. Subtypes were compared with symptoms and physiology among 2949 participants in the population-based Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study and with prognosis among 6658 MESA participants. Associations with genome-wide single-nucleotide-polymorphisms were examined.

RESULTS: The algorithm discovered six reproducible (interlearner intraclass correlation coefficient, 0.91-1.00) CT emphysema subtypes. The most common subtype in SPIROMICS, the combined bronchitis-apical subtype, was associated with chronic bronchitis, accelerated lung function decline, hospitalisations, deaths, incident airflow limitation and a gene variant near DRD1, which is implicated in mucin hypersecretion (p=1.1 ×10-8). The second, the diffuse subtype was associated with lower weight, respiratory hospitalisations and deaths, and incident airflow limitation. The third was associated with age only. The fourth and fifth visually resembled combined pulmonary fibrosis emphysema and had distinct symptoms, physiology, prognosis and genetic associations. The sixth visually resembled vanishing lung syndrome.

CONCLUSION: Large-scale unsupervised machine learning on CT scans defined six reproducible, familiar CT emphysema subtypes that suggest paths to specific diagnosis and personalised therapies in COPD and pre-COPD.

PMID:37268414 | DOI:10.1136/thorax-2022-219158