Changes In Abundance Research Articles

In-Depth Proteomic Analysis of Tissue Interstitial Fluid Reveals Biomarker Candidates Related to Varying Differentiation Statuses in Gastric Adenocarcinoma.

The proteomic heterogeneity of gastric adenocarcinoma (GC) has been extensively investigated at the bulk tissue level, which can only provide an average molecular state. In this study, we collected an in-depth quantitative proteomic dataset of tissues and interstitial fluids (ISFs) from both poorly and non-poorly differentiated GC and presented a comprehensive analysis from several perspectives. Comparison of proteomes between ISFs and tissues revealed that ISF exhibited higher abundances of proteins associated with blood microparticles, protein-lipid complexes, immunoglobulin complexes, and high-density lipoprotein particles. Also, consistent and inconsistent protein abundance changes between them were revealed by a correlation analysis. Interestingly, a more pronounced difference between tumors and normal adjacent tissues was found at the ISF level, which accurately reflected tissue properties compared to those of bulk tissue. Two ISF-derived biomarker candidates, calsyntenin-1 (CLSTN1) and prosaposin (PSAP), were identified by distinguishing patients with different differentiation statuses and were further validated in serum samples. Additionally, the silencing of CLSTN1 and PSAP was demonstrated to suppress cell proliferation, migration, and invasion in poorly differentiated gastric cancer cell lines. In summary, the ISF proteome offers a new perspective on tumor biology. This study provides a valuable resource that significantly enhances the understanding of GC and may ultimately benefit clinical practice.

Metabolomic-Based Assessment of Earthworm (Eisenia fetida) Exposure to Different Petroleum Fractions in Soils

Background/Objectives: Petroleum contamination in soil exerts toxic effects on earthworms (Eisenia fetida) through non-polar narcotic mechanisms. However, the specific toxicities of individual petroleum components remain insufficiently understood. Methods: This study investigates the effects of four petroleum components—saturated hydrocarbons, aromatic hydrocarbons, resins, and asphaltenes—on earthworms in artificially contaminated soil, utilizing a combination of biochemical biomarker analysis and metabolomics to uncover the underlying molecular mechanisms. Results: The results revealed that aromatic hydrocarbons are the most toxic fraction, with EC50 concentrations significantly lower than those of other petroleum fractions. All tested fractions triggered notable metabolic disturbances and immune responses in earthworms after 7 days of exposure, as evidenced by significant changes in metabolite abundance within critical pathways such as arginine synthesis, a-linolenic acid metabolism, and the pentose phosphate pathway. According to the KEGG pathway analysis, saturated hydrocarbon fractions induced marked changes in glycerophospholipid metabolism, and arginine and proline metabolism pathways, contributing to the stabilization of the protein structure and membrane integrity. Aromatic hydrocarbon fractions disrupted the arachidonic acid metabolic pathway, leading to increased myotube production and enhanced immune defense mechanisms. The TCA cycle and riboflavin metabolic pathway were significantly altered during exposure to the colloidal fraction, affecting energy production and cellular respiration. The asphaltene fraction significantly impacted glycolysis, accelerating energy cycling to meet stress-induced increases in energy demands. Conclusions: Aromatic hydrocarbons accounted for the highest level of toxicity among the four components in petroleum-contaminated soils. However, the contributions of other fractions to overall toxicity should not be ignored, as each fraction uniquely affects key metabolic pathways and biological functions. These findings emphasize the importance of monitoring metabolic perturbations caused by petroleum components in non-target organisms such as earthworms. They also reveal the specificity of the toxic metabolic effects of different petroleum components on earthworms.

Quantitative differences in rumen epithelium proteins and detection of lysine acetylation in lambs fed a low or high metabolizable energy diet.

Thirty-six Merino wethers (10-month-old) were fed ad libitum for 30 days two diets;1) low metabolizable energy diet (LME; 30% lucerne: 70% cereal chaff) and 2) high ME diet (HME; 40% rolled barley grain: 50% lucerne: 10% cereal chaff). Effects of diet on dry matter intake (DMI), metabolizable energy intake (MEI), liveweight (LWT), average daily gain (ADG), carcass lean or fat gain, liver and empty rumen weight and plasma metabolites were analysed. A membrane enriched protein fraction of rumen epithelium isolated enzymatically from whole depth rumen wall was quantified for each sheep using tandem mass tag mass spectrometry (TMT-MS). The presence or absence of acetylation of lysine residues on identified proteins was counted and the position of the lysine acetylation recorded. In lambs fed the HME diet, DMI (P<0.001), MEI (P<0.001), ADG (P<0.001), fat (P<0.001) and lean gain (P<0.001), as well as liver (P<0.001) and empty rumen (P<0.009) weight were greater than those fed the LME diet. Plasma glucose (P<0.001) and β hydroxybutyrate (P<0.001) at 3 and 5h after feeding was greater in HME diet than in the LME fed lambs. Changes in rumen epithelium protein abundance in the LME versus HME fed lambs were associated with metabolism in the peroxisome, protein processing in the endoplasmic reticulum (ER), valine, leucine and isoleucine degradation and carbon metabolism. Acetylation of lysine was detected in enzymes involved in glycolysis, tricarboxylic acid (TCA) cycle and fatty acid (FA) metabolism. Quantitative differences in the abundance of rumen epithelium proteins that carry out intracellular processes of energy expenditure were associated with the concentration of ME (MJ/ kg DM) in the diet of growing lambs. The detection of lysine acetylation sites suggests a difference in the ME of the diet regulates enzymatic activity in central metabolic pathways in the rumen epithelium cells.

Identification of Plasma Metabolites Responding to Oxycodone Exposure in Rats

Background: Oxycodone has an elevated abuse liability profile compared to other prescription opioid medications. However, many human and rodent metabolomics studies have not been specifically focused on oxycodone. Objectives: Investigating metabolomics changes associated with oxycodone exposure can provide insights into biochemical mechanisms of the addiction cycle and prognosis prediction. Methods: Plasma samples from 16 rats at pre-exposure and intoxication time points were profiled on the Metabolon platform. A total of 941 metabolites were characterized. We employed a k-Nearest Neighbor imputation to impute metabolites with low levels of missingness and binarized metabolites with moderate levels of missingness, respectively. Results: Of the 136 binarized metabolites, 6 showed differential abundance (FDR &lt; 0.05), including 5 that were present at pre-exposure but absent at intoxication (e.g., adenine), while linoleamide (18:2n6) exhibited the opposite behavior. Among the 798 metabolites with low levels of missingness, 364 showed significant changes between pre-exposure and intoxication (FDR &lt; 0.01), including succinate, oleamide, and sarcosine. We identified four pathways, including tryptophan metabolism, that were nominally enriched among the metabolites that change with oxycodone exposure (p &lt; 0.05). Furthermore, we identified several metabolites that showed nominal correlations with the Addiction Index (composite of oxycodone behaviors): 17 at pre-exposure and 8 at intoxication. In addition, the changes in abundance between pre-exposure and intoxication time points of 9 metabolites were nominally correlated with the Addiction Index, including sphingomyelins, methylhistidines, and glycerols. Conclusions: In summary, not only were we able to capture oxy-induced changes in metabolic pathways using easily accessible blood samples, but we also demonstrated the potential of blood metabolomics to better understand addiction liability.

Bacterial Community Structure in Soils With Fire-Deposited Charcoal Under Rotational Shifting Cultivation of Upland Rice in Northern Thailand.

Rotational shifting cultivation (RSC) is a traditional agricultural practice in mountainous areas that uses fire to clear land after cutting vegetation for cultivation. However, few studies have assessed the effect of fire-deposited charcoal on the diversity and composition of soil microbial communities, and none have been conducted in Thailand. Therefore, this study was conducted 1 year after a fire in an abandoned 12-year RSC in Chiang Mai Province, northern Thailand. Charcoal samples were collected from the surface litter layer, while charcoal-soil mixtures were taken from the surface soil (0-2 cm). Soil samples from 2 to 7 cm captured the charcoal-soluble layer, and samples from 7 to 15 cm represented soil without charcoal incorporation. The results revealed that charcoal led to higher pH and electrical conductivity in the charcoal layer, with notable differences in soil texture across layers, including the highest sand and silt content in the charcoal-mixed soil layer (0-2 cm). Soil organic matter and total nitrogen were significantly higher in the charcoal-mixed layer compared to deeper layers, indicating improved nutrient retention due to charcoal presence. Enhanced microbial diversity was observed in the charcoal and charcoal-mixed soil layers, with Proteobacteria, Chloroflexi, and Planctomycetota dominating across all soil samples. The bacterial genus Ilumatobacter exhibited significant changes in abundance in the charcoal layer. Additionally, Pseudolabrys was more abundant in charcoal-leached soil, while JG30a-KF-32 showed greater abundance in soil without charcoal. Shifts in Proteobacteria and Planctomycetota abundance were evident in the charcoal leaching and non-charcoal layers. Network analysis indicated more complex bacterial interactions in the charcoal-mixed soil layer, with reduced network complexity observed in the charcoal leaching layer and the layer without charcoal. These findings imply that charcoal provides a favorable environment for diverse and interactive bacterial communities, potentially benefiting soil health and fertility recovery in RSC fields.

Bacteriophages carry auxiliary metabolic genes related to energy, sulfur and phosphorus metabolism during a harmful algal bloom in a freshwater lake.

Cyanophages play an important role in nutrient cycling in lakes since they can modulate the metabolism of cyanobacteria. A proper understanding of the impact of cyanophage infection on the metabolism and ecology of cyanobacteria is critical during a complete cycle of harmful algal bloom (HAB). The ecology of cyanophages in marine environments has been well-delineated, but cyanophages in freshwater lakes remain less studied. Here, we studied the diversity of cyanophages and their impact on host ecology and metabolism in through the succession of HAB in Utah Lake, which is a shallow eutrophic freshwater lake, in 2019. We collected water samples at three different periods from two locations in freshwater Utah Lake. The three sampling periods represented the pre- bloom, peak- bloom, and post-bloom events. We observed that the Utah Lake virome was dominated byfamilies Myoviridae, Siphoviridae, and Podoviridae under the order Caudovirales. We detected photosystem-related genes, sulfur assimilation genes, and pho regulon (phosphorus metabolism) genes in genomes of predicted cyanophages. We were able to capture the changes in relative abundance and expression of functional genes in genomes of cyanophage at different stages of the bloom. We observed higher relative abundance and expression of cyanophage-encoded pho-regulon genes in the “pre-bloom” period. The higher expression of pho-regulon genes in P-limited ecosystem of Utah Lake indicated the possible contribution of cyanophage to enhance the fitness of the host cyanobacteria. Our study provides some insightful findings on the role of cyanophages in controlling the ecology and relative abundance of host cyanobacteria in freshwater lakes.

Effects of traditional Chinese medicine Zuo-Gui-Wan on gut microbiota in an osteoporotic mouse model.

The target and mechanism of oral traditional Chinese medicine (TCM) have been important research directions for a long time. The close relationship between osteoporosis and gut microbiota (GM) has been confirmed. However, the relevance of oral TCM and the "Gut-Bone Axis" is still poorly understood. Twenty-one SPF C57BL/6J female mice were divided into sham (Sham), ovariectomized (OVX), and Zuo-Gui-Wan-treated (ZGW, 1.4g/kg) groups. The osteoporosis mouse model was established through ovariectomy. After eight weeks of Zuo-Gui-Wan treatment via gavage, serum calcium, phosphorus, ALT, AST, CREA, and other biochemical indicators were measured. Subsequently, Micro-CT, HE staining, and analysis of gut microbiota were conducted to further explore the potential mechanism. The anti-osteoporotic effects of ZGW were confirmed through micro-CT, histological, and biochemical tests in an OVX-induced osteoporosis mouse model. ZGW treatment also alters the diversity and composition of the gut microbiota and altered the Firmicutes/Bacteroidetes ratio. Further analysis reveals a correlation between specific bacterial groups and serum indicators. Mfuzz clustering analysis and metagenomeSeq analysis identified important microbiota species that were rescued or modulated by ZGW treatment. These findings suggest that changes in gut microbiota abundance may be linked to ZGW's ability to improve osteoporosis. This study provides new insights into how ZGW treats osteoporosis, though further research is needed to clarify the mechanisms by which specific gut microbiota influence bone health.

The immunosenescence clock: A new method for evaluating biological age and predicting mortality risk.

Precisely assessing an individual's immune age is critical for developing targeted aging interventions. Although traditional methods for evaluating biological age, such as the use of cellular senescence markers and physiological indicators, have been widely applied, these methods inherently struggle to capture the full complexity of biological aging. We propose the concept of an 'immunosenescence clock' that evaluates immune system changes on the basis of changes in immune cell abundance and omics data (including transcriptome and proteome data), providing a complementary indicator for understanding age-related physiological transformations. Rather than claiming to definitively measure biological age, this approach can be divided into a biological age prediction clock and a mortality prediction clock. The main function of the biological age prediction clock is to reflect the physiological state through the transcriptome data of peripheral blood mononuclear cells (PBMCs), whereas the mortality prediction clock emphasizes the ability to identify people at high risk of mortality and disease. We hereby present nearly all of the immunosenescence clocks developed to date, as well as their functional differences. Critically, we explicitly acknowledge that no single diagnostic test can exhaustively capture the intricate changes associated with biological aging. Furthermore, as these biological functions are based on the acceleration or delay of immunosenescence, we also summarize the factors that accelerate immunosenescence and the methods for delaying it. A deep understanding of the regulatory mechanisms of immunosenescence can help establish more accurate immune-age models, providing support for personalized longevity interventions and improving quality of life in old age.

Relative quantification of proteins and post-translational modifications in proteomic experiments with shared peptides: a weight-based approach.

Bottom-up mass spectrometry-based proteomics studies changes in protein abundance and structure across conditions. Since the currency of these experiments are peptides, ie subsets of protein sequences that carry the quantitative information, conclusions at a different level must be computationally inferred. The inference is particularly challenging in situations where the peptides are shared by multiple proteins or post-translational modifications. While many approaches infer the underlying abundances from unique peptides, there is a need to distinguish the quantitative patterns when peptides are shared. We propose a statistical approach for estimating protein abundances, as well as site occupancies of post-translational modifications, based on quantitative information from shared peptides. The approach treats the quantitative patterns of shared peptides as convex combinations of abundances of individual proteins or modification sites, and estimates the abundance of each source in a sample together with the weights of the combination. In simulation-based evaluations, the proposed approach improved the precision of estimated fold changes between conditions. We further demonstrated the practical utility of the approach in experiments with diverse biological objectives, ranging from protein degradation and thermal proteome stability, to changes in protein post-translational modifications. The approach is implemented in an open-source R package MSstatsWeightedSummary. The package is currently available at https://github.com/Vitek-Lab/MSstatsWeightedSummary (doi:10.5281/zenodo.14662989). Code required to reproduce the results presented in this article can be found in a repository https://github.com/mstaniak/MWS_reproduction (doi:10.5281/zenodo.14656053). Supplementary data are available at Bioinformatics online.

Off-target drift of the herbicide dicamba disrupts plant-pollinator interactions via novel pathways.

While herbicide use in agriculture is expected to have many effects on surrounding weed communities, it is largely unknown how plant exposure to sublethal doses of herbicide may subsequently impact plant-pollinator interactions. We tested the hypothesis that sublethal herbicide exposure indirectly alters plant-pollinator interactions through changes in plant traits, and specifically through alterations in floral display. Using a common garden experiment, we exposed 11 weed species to the herbicide dicamba and examined the potential for changes in pollinator abundance and patterns of pollinator visitation as well as alterations to plant traits. We found variation among plant species in the extent of damage from dicamba drift, and variation in size, flowering time, and flower displays, with some plant species showing negative impacts and others showing little effect. Pollinator frequencies were reduced in dicamba-exposed plots, and pollinator visits were reduced for some weed species yet not for others. Structural equation modeling revealed that the relationship between flower display and pollinator visits was disrupted in the presence of dicamba. Our study provides the most comprehensive picture to date of the impacts of herbicide drift on plant-pollinator interactions, with findings that highlight an underappreciated role of services supplied by weedy communities.

SEC-MX: an approach to systematically study the interplay between protein assembly states and phosphorylation

A protein’s molecular interactions and post-translational modifications (PTMs), such as phosphorylation, can be co-dependent and reciprocally co-regulate each other. Although this interplay is central for many biological processes, a systematic method to simultaneously study assembly states and PTMs from the same sample is critically missing. Here, we introduce SEC-MX (Size Exclusion Chromatography fractions MultipleXed), a global quantitative method combining Size Exclusion Chromatography and PTM-enrichment for simultaneous characterization of PTMs and assembly states. SEC-MX enhances throughput, allows phosphopeptide enrichment, and facilitates quantitative differential comparisons between biological conditions. Conducting SEC-MX on HEK293 and HCT116 cells, we generate a proof-of-concept dataset, mapping thousands of phosphopeptides and their assembly states. Our analysis reveals intricate relationships between phosphorylation events and assembly states and generates testable hypotheses for follow-up studies. Overall, we establish SEC-MX as a valuable tool for exploring protein functions and regulation beyond abundance changes.

Comprehensive transcriptomic analysis reveals turnip mosaic virus infection and its aphid vector Myzus persicae cause large changes in gene regulatory networks and co-transcription of alternative spliced mRNAs in Arabidopsis thaliana.

Virus infection and herbivory can alter the expression of stress-responsive genes in plants. This study employed high-throughput transcriptomic and alternative splicing analysis to understand the separate and combined impacts on host gene expression in Arabidopsis thaliana by Myzus persicae (green peach aphid), and turnip mosaic virus (TuMV). By investigating changes in transcript abundance, the data shows that aphids feeding on virus infected plants intensify the number of differentially expressed stress responsive genes compared to challenge by individual stressors. This study presents evidence that the combination of virus-vector-host interactions induces significant changes in hormone and secondary metabolite biosynthesis, as well as downstream factors involved in feedback loops within hormone signaling pathways. This study also shows that gene expressions are regulated through alternative pre-mRNA splicing and the use of alternative transcription start and termination sites. These combined data suggest that complex genetic changes occur as plants adapt to the combined challenges posed by aphids and the viruses they vector. This study also provides more advanced analyses that could be used in the future to dissect the genetic mechanisms mediating tripartite interactions and inform future breeding programs.

Impact of Local Air Pressure on Ion Mobilities and Data Consistency in diaPASEF-Based High Throughput Proteomics.

Data-independent acquisition (DIA) on ion mobility mass spectrometers enables deep proteome coverage and high data completeness in large-scale proteomics studies. For advanced acquisition schemes such as parallel accumulation serial fragmentation-based DIA (diaPASEF) stability of ion mobility (1/K0) over time is crucial for consistent data quality. We found that minor changes in environmental air pressure systematically affect the vacuum pressure in the TIMS analyzer, causing ion mobility shifts. By comparing experimental ion mobilities with historical weather data, we attributed observed drifts to fluctuations in the ground air pressure. Moderate air pressure changes of e.g. fifteen mbar induce ion mobility shifts of 0.025 Vs/cm2. These drifts negatively impact peptide quantification across consecutively acquired samples due to drift-dependent abundance changes and increased missing values for ions located at the boundaries of diaPASEF isolation windows, which cannot be corrected by postprocessing. To address this, we applied an in-batch mobility autocalibration feature on a run-wise basis, leading to full elimination of ion mobility drifts.

Proteomic Variation in the Oral Secretion of Spodoptera exigua and Spodoptera littoralis Larvae in Response to Different food Sources

The Spodoptera genus is defined as the pest-rich genus because it contains some of the most destructive lepidopteran crop pests, characterized by a wide host range. During feeding, the caterpillars release small amounts of oral secretion (OS) onto the wounded leaves. This secretion contains herbivore-induced molecular patterns (HAMPs) that activate the plant defense response, as well as effectors that may inhibit or diminish the plant’s anti-herbivory response. In this study, we explored the protein components of the OS of two Spodoptera species, Spodoptera exigua and Spodoptera littoralis. We identified 336 and 276 proteins, respectively, with a major role in digestion. Using a label-free quantitative proteomics approach, we investigated changes in protein abundance in the OS of both species after switching from a laboratory artificial diet to detached pepper and tomato leaves. Several proteins, such as various lipases, polycalin and a β-1,3-glucan binding protein, were more abundant in the OS of leaf-fed larvae in both species. Conversely, a tryptophan-aspartic acid (WD)-repeat containing protein significantly decreased upon feeding on plant leaves in both species. Phenotypic plasticity dependent on each Spodoptera-plant combination was observed for several peptidases, potentially related to the need to overcome the effects of proteinase inhibitors differentially produced by the two plant species, and for several REPAT proteins, possibly related to the specific modulation of each Spodoptera-plant interaction. Altogether, our results provide useful information for understanding the interaction of these two polyphagous Spodoptera species with the host plants, and help to identify evolutionary traits that may influence the outcome of herbivory in each of these two related species.

Developmental synchrony and extraordinary multiplication rates in pathogenic organisms.

The multiplication rates of pathogenic organisms influence disease progression, efficacy of immunity and therapeutics, and potential for within-host evolution. Thus, accurate estimates of multiplication rates are essential for biological understanding. We recently showed that common methods for inferring multiplication rates from malaria infection data substantially overestimate true values (i.e. under simulated scenarios), providing context for extraordinarily large estimates in human malaria parasites. A key unknown is whether this bias arises specifically from malaria parasite biology or represents a broader concern. Here, we identify the potential for biased multiplication rate estimates across pathogenic organisms with different developmental biology by generalizing a within-host malaria model. We find that diverse patterns of developmental sampling bias-the change in detectability over developmental age-reliably generate overestimates of the fold change in abundance, obscuring not just true growth rates but potentially even whether populations are expanding or declining. This pattern emerges whenever synchrony-the degree to which development is synchronized across the population of pathogenic organisms comprising an infection-decays with time. Only with simulated increases in synchrony do we find noticeable underestimates of multiplication rates. Obtaining robust estimates of multiplication rates may require accounting for diverse patterns of synchrony in pathogenic organisms.This article is part of the Theo Murphy meeting issue 'Circadian rhythms in infection and immunity'.

Understanding Marine Biodiversity Shifts in Southeast Greenland with Indigenous and Local Knowledge

Abstract We contribute to the identification of marine biodiversity status and changes in the coastal area of Southeast Greenland through consultation with holders of local and Indigenous knowledge (LEK/IK). Through in-depth interviews with coastal fishers and hunters in the Ammassalik area, we explore a range of changes to known and new species in relation to ecosystem dynamics. Key observations include diminishing presence of polar cod (Boreogadus saida), new abundance of known fish species (Gadus morhua, Salvelinus alpinus, Reinhardtius hippoglossoides, Cyclopterus lumpus), inflow of new/rare species of whales, fish, and shellfish (Oncorhynchus gorbuscha, Lamna nasus, Paralithodes camtschaticus, Physeter macrocephalus, Globicephala melas, Megaptera novaeangliae, Phocoena phocoena), and increasing absence in the fjords of some local seal species (Cystophora cristata and Pusa hispida). Observed changes in local abundances are understood with reference to the physical changes in temperature, ocean currents, glacier melt, and snowfall. Changed dynamics in prey-predator relationships are observed to mediate the local presence of target species. Other environmental changes include an influx of new food items in food chains and increased seaweed growth. Our study confirms the relevance and timeliness of systematically incorporating local and Indigenous knowledge to enhance the understanding of coastal marine dynamics in the context of climate change and the geographical ‘opening’ of the East Greenlandic region.

MODE: A Web Application for Interactive Visualization and Exploration of Omics Data.

Studies generating transcriptomics, proteomics, lipidomics, and metabolomics (colloquially referred to as "omics") data allow researchers to find biomarkers or molecular targets or understand complex biological structures and functions by identifying changes in biomolecule abundance and expression between experimental conditions. Omics data are multidimensional, and oftentimes summarization techniques such as principal component analysis (PCA) are used to identify high-level patterns in data. Though useful, these summaries do not allow exploration of detailed patterns in omics data that may have biological relevance. The use of interactive HTML displays with plots allows researchers to interact with omics data at a detailed level, but building these displays requires significant coding expertise. To overcome this barrier, the software MODE was built to empower users to build their own interactive HTML displays to support scientific discovery. These displays are easily shareable, do not depend on a specific operating system, and allow users to sort and filter plots by categorical or numerical variables called metas. MODE allows users to build and share these displays with several options for plot design and meta selection. The MODE web application and its capabilities are presented and then demonstrated on lipidomics data from a leaf wounding study.

A post-injury immune challenge with lipopolysaccharide following adult traumatic brain injury alters neuroinflammation and the gut microbiome acutely, but has little effect on chronic outcomes.

Patients with a traumatic brain injury (TBI) are susceptible to hospital-acquired infections, presenting a significant challenge to an already-compromised immune system. The consequences and mechanisms by which this dual insult worsens outcomes are poorly understood. This study aimed to explore how a systemic immune stimulus (lipopolysaccharide, LPS) influences outcomes following experimental TBI in young adult mice. Male and female C57Bl/6 J mice underwent controlled cortical impact or sham surgery, followed by 1 mg/kg i.p. LPS or saline-vehicle at 4 days post-TBI, before behavioral assessment and tissue collection at 6 h, 24 h, 7 days or 6 months. LPS induced acute sickness behaviors including weight loss, transient hypoactivity, and increased anxiety-like behavior. Early systemic immune activation by LPS was confirmed by increased spleen weight and serum cytokines. In brain tissue, gene expression analysis revealed a time course of inflammatory immune activation in TBI or LPS-treated mice (e.g., IL-1β, IL-6, CCL2, TNFα), which was exacerbated in TBI + LPS mice. This group also presented with fecal microbiome dysbiosis at 24 h post-LPS, with reduced bacterial diversity and changes in the relative abundance of key bacterial genera associated with sub-acute neurobehavioral and immune changes. Chronically, TBI induced hyperactivity and cognitive deficits, brain atrophy, and increased seizure susceptibility, similarly in vehicle and LPS-treated groups. Together, findings suggest that an immune challenge with LPS early after TBI, akin to a hospital-acquired infection, alters the acute neuroinflammatory response to injury, but has no lasting effects. Future studies could consider more clinically-relevant models of infection to build upon these findings.

Osteopenia Metabolomic Biomarkers for Early Warning of Osteoporosis.

Introduction: This study aimed to capture the early metabolic changes before osteoporosis occurs and identify metabolomic biomarkers at the osteopenia stage for the early prevention of osteoporosis. Materials and Methods: Metabolomic data were generated from normal, osteopenia, and osteoporosis groups with 320 participants recruited from the Nicheng community in Shanghai. We conducted individual edge network analysis (iENA) combined with a random forest to detect metabolomic biomarkers for the early warning of osteoporosis. Weighted Gene Co-Expression Network Analysis (WGCNA) and mediation analysis were used to explore the clinical impacts of metabolomic biomarkers. Results: Visual separations of the metabolic profiles were observed between three bone mineral density (BMD) groups in both genders. According to the iENA approach, several metabolites had significant abundance and association changes in osteopenia participants, confirming that osteopenia is a critical stage in the development of osteoporosis. Metabolites were further selected to identify osteopenia (nine metabolites in females; eight metabolites in males), and their ability to discriminate osteopenia was improved significantly compared to traditional bone turnover markers (BTMs) (female AUC = 0.717, 95% CI 0.547-0.882, versus BTMs: p = 0.036; male AUC = 0.801, 95% CI 0.636-0.966, versus BTMs: p = 0.007). The roles of the identified key metabolites were involved in the association between total fat-free mass (TFFM) and osteopenia in females. Conclusion: Osteopenia was identified as a tipping point during the development of osteoporosis with metabolomic characteristics. A few metabolites were identified as candidate early-warning biomarkers by machine learning analysis, which could indicate bone loss and provide new prevention guidance for osteoporosis.

Genome-Wide Characterization of Extrachromosomal Circular DNA in the Midgut of BmCPV-Infected Silkworms and Its Potential Role in Antiviral Responses.

Extrachromosomal circular DNAs (eccDNAs) has been found to be widespread and functional in various organisms. However, comparative analyses of pre- and post-infection of virus are rarely known. Herein, we investigated the changes in expression patterns of eccDNA following infection with Bombyx mori cytoplasmic polyhedrosis virus (BmCPV) and explore the role of eccDNA in viral infection. Circle-seq was used to analyze eccDNAs in the midgut of BmCPV-infected and BmCPV-uninfected silkworms. A total of 5508 eccDNAs were identified, with sizes varying from 72 bp to 17 kb. Most of eccDNAs are between 100 to 1000 bp in size. EccDNA abundance in BmCPV-infected silkworms was significantly higher than in BmCPV-uninfected silkworms. GO and KEGG analysis of genes carried by eccDNAs reveals that most are involved in microtubule motor activity, phosphatidic acid binding, cAMP signaling pathway, and pancreatic secretion signaling pathways. Several eccDNAs contain sequences of the transcription factor SOX6, sem-2, sp8b, or Foxa2. Association analysis of eccDNA-mRNA/miRNA/circRNA revealed that some highly expressed genes are transcribed from relevant sequences of eccDNA and the transcription of protein coding genes influenced the frequency of eccDNA. BmCPV infection resulted in changes in the expression levels of six miRNAs, but no known miRNAs with altered expression levels due to changes in eccDNA abundance were identified. Moreover, it was found that 1287 and 924 sequences representing back-spliced junctions of circRNAs were shared by the junctions of eccDNAs in the BmCPV-infected and uninfected silkworms, respectively, and some eccDNAs loci were shared by circRNAs on Chromosomes 2, 7, 11, 14, and 24, suggesting some eccDNAs may exert its function by being transcribed into circRNAs. These findings suggest that BmCPV infection alter the expression pattern of eccDNAs, leading to changes in RNA transcription levels, which may play roles in regulating BmCPV replication. In the future, further experiments are needed to verify the association between eccDNA-mRNA/miRNA/circRNA and its function in BmCPV infection.