Gene length corrected trimmed mean of M-values (GeTMM) processing of RNA-seq data performs similarly in intersample analyses while improving intrasample comparisons

Role of PRC2 in the stochastic expression of Aire target genes and development of mimetic cells in the thymus

The transcriptional targets of Aire and the mechanisms controlling their expression in medullary thymic epithelial cells (mTECs) need to be clarified to understand Aire's tolerogenic function. By using a multi-omics single-cell approach coupled with deep scRNA-seq, we examined how Aire controls the transcription of a wide variety of genes in a small fraction of Aire-expressing cells. We found that chromatin repression by PRC2 is an important step for Aire to achieve stochastic gene expression. Aire unleashed the silenced chromatin configuration caused by PRC2, thereby increasing the expression of its functional targets. Besides this preconditioning for Aire's gene induction, we demonstrated that PRC2 also controls the composition of mTECs that mimic the developmental trait of peripheral tissues, i.e., mimetic cells. Of note, this action of PRC2 was independent of Aire and it was more apparent than Aire. Thus, our study uncovered the essential role of polycomb complex for Aire-mediated promiscuous gene expression and the development of mimetic cells.

Clinicopathological and molecular characterization of inflammatory breast cancer, the prospective INFLAME registry study

Inflammatory breast cancer (IBC) is rare, with challenging diagnostics and unfavorable outcomes. Therefore, more molecular insight into IBC is needed. The comprehensive Dutch prospective INFLAME registry related IBC follow-up and treatment to histopathology and molecular analysis. Of consecutive patients, nationwide identified with newly diagnosed IBC, clinicopathological, treatment and outcome data were collected. Histopathology and RNA-sequencing were related to outcome. 125 IBC patients were enrolled. Forty-one (34%) patients had HER2 + , and 31 (25%) had triple-negative IBC. The estimated 3-year OS was 78% in M0 IBC and 29% in M1. PFS was worst in triple-negative IBC (median 7.9 vs 16.3 and 15.8 months in M1 HER2+ and HR + /HER2- IBC). DFS and OS in M0 IBC were better with guideline-concordant trimodal therapy than without (HR 0.15 and 0.15; p = 0.000005 and 0.00038). The unique prospective INFLAME confirms unfavorable IBC characteristics and outcomes. International efforts may support guideline adherence and identify IBC-specific targets.

Fantastic genes and where to find them expressed in CHO

The transcriptome of Chinese hamster ovary (CHO) cells plays a crucial role in determining cellular characteristics that are essential for biopharmaceutical applications. RNA-sequencing has been extensively used to profile gene expression patterns, aiming to gain a better understanding of intracellular behavior and mechanisms. Individual datasets, however, do not provide a comprehensive overview and characterization of the CHO cell's transcriptome, such that the fundamental structure of the transcriptome remains unknown. Using 15 RNA-sequencing datasets, encompassing almost 300 samples of various experimental setups, conditions and cell lines, we explore and classify the protein-coding transcriptome of CHO cells. Differences in cell line lineages are found to be the primary source of variation in transcribed genes. By employing a novel approach, we identified the core transcriptome that is ubiquitously expressed in all cell lines and culture conditions, as well as genes that remain entirely non-expressed. Additionally, we identified a set of genes that may be active or inactive depending on different conditions, which are linked to biological processes including translation as well as immune and stress response. Lastly, by integrating chromatin states derived from histone modifications, we provided additional context on the epigenetic level that supports our protein-coding gene classification. Our study offers a comprehensive insight into the CHO cell transcriptome and lays the foundation for future research into cellular adaptation to changing conditions and the development of phenotypes.

Limosilactobacillus reuteri promotes the expression and secretion of enteroendocrine- and enterocyte-derived hormones

Intestinal microbes can beneficially impact host physiology, prompting investigations into the therapeutic usage of such microbes in a range of diseases. For example, human intestinal microbe Limosilactobacillus reuteri strains ATCC PTA 6475 and DSM 17938 are being considered for use for intestinal ailments, including colic, infection, and inflammation, as well as for non-intestinal ailments, including osteoporosis, wound healing, and autism spectrum disorder. While many of their beneficial properties are attributed to suppressing inflammatory responses, we postulated that L. reuteri may also regulate intestinal hormones to affect physiology within and outside of the gut. To determine if L. reuteri secreted factors impact the secretion of enteric hormones, we treated an engineered jejunal organoid line, NGN3-HIO, which can be induced to be enriched in enteroendocrine cells, with L. reuteri 6475 or 17938 conditioned medium and performed transcriptomics. Our data suggest that these L. reuteri strains affect the transcription of many gut hormones, including vasopressin and luteinizing hormone subunit beta, which have not been previously recognized as produced in the gut epithelium. Moreover, we find that these hormones appear to be produced in enterocytes, in contrast to canonical gut hormones produced in enteroendocrine cells. Finally, we show that L. reuteri conditioned media promote the secretion of enteric hormones, including serotonin, GIP, PYY, vasopressin, and luteinizing hormone subunit beta, and identify by metabolomics metabolites potentially mediating these effects on hormones. These results support L. reuteri affecting host physiology through intestinal hormone secretion, thereby expanding our understanding of the mechanistic actions of this microbe.

Environmental matrix and moisture influence soil microbial phenotypes in a simplified porous media incubation

Soil moisture and porosity regulate microbial metabolism by influencing factors, such as system chemistry, substrate availability, and soil connectivity. However, accurately representing the soil environment and establishing a tractable microbial community that limits confounding variables is difficult. Here, we use a reduced-complexity microbial consortium grown in a glass bead porous media amended with chitin to test the effects of moisture and a structural matrix on microbial phenotypes. Leveraging metagenomes, metatranscriptomes, metaproteomes, and metabolomes, we saw that our porous media system significantly altered microbial phenotypes compared with the liquid incubations, denoting the importance of incorporating pores and surfaces for understanding microbial phenotypes in soils. These phenotypic shifts were mainly driven by differences in expression of Streptomyces and Ensifer, which included a significant decrease in overall chitin degradation between porous media and liquid. Our findings suggest that the success of Ensifer in porous media is likely related to its ability to repurpose carbon via the glyoxylate shunt amidst a lack of chitin degradation byproducts while potentially using polyhydroxyalkanoate granules as a C source. We also identified traits expressed by Ensifer and others, including motility, stress resistance, and carbon conservation, that likely influence the metabolic profiles observed across treatments. Together, these results demonstrate that porous media incubations promote structure-induced microbial phenotypes and are likely a better proxy for soil conditions than liquid culture systems. Furthermore, they emphasize that microbial phenotypes encompass not only the multi-enzyme pathways involved in metabolism but also include the complex interactions with the environment and other community members.IMPORTANCESoil moisture and porosity are critical in shaping microbial metabolism. However, accurately representing the soil environment in tractable laboratory experiments remains a challenging frontier. Through our reduced complexity microbial consortium experiment in porous media, we reveal that predicting microbial metabolism from gene-based pathways alone often falls short of capturing the intricate phenotypes driven by cellular interactions. Our findings highlight that porosity and moisture significantly affect chitin decomposition, with environmental matrix (i.e., glass beads) shifting community metabolism towards stress tolerance, reduced resource acquisition, and increased carbon conservation, ultimately invoking unique microbial strategies not evident in liquid cultures. Moreover, we find evidence that changes in moisture relate to community shifts regarding motility, transporters, and biofilm formation, which likely influence chitin degradation. Ultimately, our incubations showcase how reduced complexity communities can be informative of microbial metabolism and present a useful alternative to liquid cultures for studying soil microbial phenotypes.

A Drosophila model of mucopolysaccharidosis IIIB

Mucopolysaccharidosis type IIIB is a rare lysosomal storage disorder caused by defects in alpha-N-acetylglucosaminidase (NAGLU) and characterized by severe effects in the central nervous system. Mutations in NAGLU cause accumulation of partially degraded heparan sulfate in lysosomes. The consequences of these mutations on whole-genome gene expression and their causal relationships to neural degeneration remain unknown. Here, we used the functional Drosophila melanogaster ortholog of NAGLU, Naglu, to develop a fly model for MPS IIIB induced by gene deletion (NagluKO), missense (NagluY160C), and nonsense (NagluW422X) mutations. We used the Drosophila activity monitoring system to analyze activity and sleep and found sex- and age-dependent hyperactivity and sleep defects in mutant flies. Fluorescence microscopy on mutant fly brains using Lysotracker dye revealed a significant increase in acidic compartments. Differentially expressed genes determined from RNA sequencing of fly brains are involved in biological processes that affect nervous system development. A genetic interaction network constructed using known interacting partners of these genes consists of 2 major subnetworks, one of which is enriched in genes associated with synaptic function and the other with neurodevelopmental processes. Our data indicate that lysosomal dysfunction arising from disruption of heparan sulfate breakdown has widespread effects on the steady state of intracellular vesicle transport, including vesicles associated with synaptic transmission. Evolutionary conservation of fundamental biological processes predicts that the Drosophila model of mucopolysaccharidosis type IIIB can serve as an in vivo system for the future development of therapies for mucopolysaccharidosis type IIIB and related disorders.

Eggs-posed: revision of Schistosoma mansoni venom allergen-like proteins unveils new genes and offers new insights into egg-host interactions

BACKGROUND

Venom allergen-like proteins (VALs) are abundant in the excretory-secretory products (ESPs) of numerous parasitic helminths and have been extensively studied for over 30 years because of their potential to interact with host systems. Despite substantial research, however, the precise functions of these proteins remain largely unresolved. Schistosomes, parasites of the circulatory system, are no exception, with 29 SmVAL genes identified in the genome of Schistosoma mansoni to date. The eggs of these parasites, as primary pathogenic agents, interact directly with host tissues and release excretory-secretory products that aid their egress from the host. Although SmVALs have been detected in the egg secretome in the past, direct evidence of their secretion and functional interaction with host molecules has never been demonstrated. These findings fuel the ongoing debate as to whether egg-expressed SmVALs interact with the mammalian host or are rather miracidial proteins synthesized within the egg during larval development.

RESULTS

Based on complete revision of the SmVAL family and an associated robust transcriptomic meta-analysis of gene expression across the life cycle, we show that many of SmVAL genes, including 6 newly identified genes, are expressed in the infective larvae-producing stages (eggs and sporocysts). Following localization of two "egg-specific" SmVAL9 and SmVAL29 did not prove active secretion of these molecules into surrounding tissues but were aligned with miracidial structures interfacing with the molluscan host, specifically the larval surface and penetration glands. Finally, we show the complete lack of interactions between candidate SmVAL proteins and an array of 755 human cell receptors via a state-of-the-art SAVEXIS screen.

CONCLUSIONS

Overall, we conclude that these "egg" SmVALs are not involved in direct host‒parasite interactions in the mammalian host and are rather proteins employed during intermediate host invasion. Our study revisits and updates the SmVAL gene family, highlighting the limitations of in silico protein function predictions while emphasizing the need for up-to-date datasets and tools together with experimental validation in host-parasite interactions. By uncovering the diversity, expression patterns, and interaction dynamics of SmVALs, we open new avenues for understanding host manipulation and reevaluating orthologous proteins in other helminths.

Group a Streptococcus remains viable inside fibrin clots and gains access to human plasminogen for subsequent fibrinolysis and dissemination

Group A Streptococcus (GAS) is a major human pathogen that causes several invasive diseases including necrotizing fasciitis. The host coagulation cascade initiates fibrin clots to sequester bacteria to prevent dissemination into deeper tissues. GAS, especially skin-tropic bacterial strains, utilize specific virulence factors, plasminogen binding M-protein (PAM) and streptokinase (SK), to manipulate hemostasis and activate plasminogen to cause fibrinolysis and fibrin clot escape. A major unresolved question regards the temporal dynamics of how GAS enmeshed in a fibrin clot can access plasminogen for clot dissolution and eventual dissemination. Here, we reveal through live imaging studies that GAS trapped inside a fibrin clot can remain viable in a latent state, until access to plasminogen activates fibrinolysis and dissemination. RNA-sequencing (RNA-seq) analysis shows marked changes in the wild-type (WT)-GAS transcriptome from the time bacteria were enmeshed inside the clot (4 h) to when dissemination was initiated (8 h). To gain a more fully realized model of how GAS trapped in fibrin clots can disseminate in the blood system, we utilized a novel 3D endothelial microfluidic device to demonstrate that GAS is fully capable of fibrinolysis in an endothelial environment, revealing a major underappreciated route by which GAS may cause more invasive outcomes. Our findings reveal for the first time that GAS can engage a latent, growth-suspended phase whereby physical structures such as fibrin clots that immobilize an invading pathogen allow bacteria to remain viable until sufficient access to plasminogen allows it to initiate fibrinolysis and escape into surrounding blood system and tissues.

IMPORTANCE

Group A Streptococcus (GAS) is a human-specific bacterial pathogen that causes infections ranging in severity from mild to severe infections that can often be fatal. To protect the host, the innate immune system creates fibrin clots to trap bacteria and prevent deeper spread. GAS produces several factors that can initiate the dissolution of these fibrin clots to spread to deeper tissues, but we lack specific understanding of the timing of these events. Our studies demonstrate for the first time that GAS can delay their escape from fibrin clots to gain access to deeper tissues during infection, suggesting a key strategy that GAS utilize to cause more invasive disease.

The Convergent Evolution of Hummingbird Pollination Results in Repeated Floral Scent Loss Through Gene Downregulation

The repeated evolution of the same trait in different lineages provides powerful natural experiments to study the phenotypic and genotypic predictability of trait gain and loss. A fascinating example is the repeated evolution of hummingbird pollination in plant lineages in the Americas, a widespread and often unidirectional phenomenon. The spiral gingers in the genus Costus are ancestrally bee pollinated, and hummingbird pollination has evolved multiple times independently in the tropical Americas. These pollinator transitions are accompanied by predictable morphological and color changes, but the changes in floral scent have not been described. In this study, we describe the floral scent composition of 30 species of Costus sampled across the phylogeny to understand how floral scent has evolved across the genus with respect to pollinator transitions. We then combine transcriptomics and genomics to identify gene expression differences and gene family evolution associated with pollinator transitions. We show that hummingbird-pollinated species have mostly lost their floral scent, whereas bee-pollinated species exhibit either floral scent maintenance or, in some cases, gains of more diverse scent profiles. We find the floral scent loss appears to be due to gene downregulation rather than pseudogenization. The remarkable consistency of scent loss in hummingbird-pollinated species highlights the shared strong selection pressures experienced by these lineages. Even species with more recent transitions from bee to hummingbird pollination exhibit scent loss, highlighting the rapid breakdown of scent emission following pollinator transitions. This research highlights the capacity for rapid changes when selection pressures are strong through downregulation of floral scent genes.

Oncogenic PIK3CA corrupts growth factor signaling specificity

Technical limitations have prevented understanding of how growth factor signals are encoded in distinct activity patterns of the phosphoinositide 3-kinase (PI3K)/AKT pathway, and how this is altered by oncogenic pathway mutations. We introduce a kinetic, single-cell framework for precise calculations of PI3K-specific information transfer for different growth factors. This features live-cell imaging of PI3K/AKT activity reporters and multiplexed CyTOF measurements of PI3K/AKT and RAS/ERK signaling markers over time. Using this framework, we found that the PIK3CAH1047R oncogene was not a simple, constitutive activator of the pathway as often presented. Dose-dependent expression of PIK3CAH1047R in human cervical cancer and induced pluripotent stem cells corrupted the fidelity of growth factor-induced information transfer, with preferential amplification of epidermal growth factor receptor (EGFR) signaling responses compared to insulin-like growth factor 1 (IGF1) and insulin receptor signaling. PIK3CAH1047R did not only shift these responses to a higher mean but also enhanced signaling heterogeneity. We conclude that oncogenic PIK3CAH1047R corrupts information transfer in a growth factor-dependent manner and suggest new opportunities for tuning of receptor-specific PI3K pathway outputs for therapeutic benefit.

Identification of a global gene expression signature associated with the genetic risk of catastrophic fracture in iPSC-derived osteoblasts from Thoroughbred horses

Bone fractures are a significant problem in Thoroughbred racehorses. The risk of fracture is influenced by both genetic and environmental factors. To determine the biological processes that are affected in genetically susceptible horses, we utilised polygenic risk scoring to establish induced pluripotent stem cells (iPSCs) from horses at high and low genetic risk. RNA-sequencing on iPSC-derived osteoblasts revealed 112 genes that were significantly differentially expressed. Forty-three of these genes have known roles in bone, 27 are not yet annotated in the equine genome and 42 currently have no described role in bone. However, many of the proteins encoded by the known and unknown genes have reported interactions. Functional enrichment analyses revealed that the differentially expressed genes were overrepresented in processes regulating the extracellular matrix and pathways known to be involved in bone remodelling and bone diseases. Gene set enrichment analysis also detected numerous biological processes and pathways involved in glycolysis with the associated genes having a higher expression in the iPSC-osteoblasts from horses with low polygenic risk scores for fracture. Therefore, the differentially expressed genes may be relevant for maintaining bone homeostasis and contribute to fracture risk. A deeper understanding of the consequences of mis-regulation of these genes and the identification of the DNA variants which underpin their differential expression may reveal more about the molecular mechanisms which are involved in equine bone health and fracture risk.

Metabolic interactions underpinning high methane fluxes across terrestrial freshwater wetlands

Current estimates of wetland contributions to the global methane budget carry high uncertainty, particularly in accurately predicting emissions from high methane-emitting wetlands. Microorganisms drive methane cycling, but little is known about their conservation across wetlands. To address this, we integrate 16S rRNA amplicon datasets, metagenomes, metatranscriptomes, and annual methane flux data across 9 wetlands, creating the Multi-Omics for Understanding Climate Change (MUCC) v2.0.0 database. This resource is used to link microbiome composition to function and methane emissions, focusing on methane-cycling microbes and the networks driving carbon decomposition. We identify eight methane-cycling genera shared across wetlands and show wetland-specific metabolic interactions in marshes, revealing low connections between methanogens and methanotrophs in high-emitting wetlands. Methanoregula emerged as a hub methanogen across networks and is a strong predictor of methane flux. In these wetlands it also displays the functional potential for methylotrophic methanogenesis, highlighting the importance of this pathway in these ecosystems. Collectively, our findings illuminate trends between microbial decomposition networks and methane flux while providing an extensive publicly available database to advance future wetland research.

A reproducibility study on invasion in small pulmonary adenocarcinoma according to the WHO and a modified classification, supported by biomarkers

OBJECTIVES

Evaluating invasion in non-mucinous adenocarcinoma (NMA) of the lung is crucial for accurate pT-staging. This study compares the World Health Organization (WHO) with a recently modified NMA classification.

MATERIALS AND METHODS

A retrospective case-control study was conducted on small NMA pT1N0M0 cases with a 5-year follow-up. Seventy cases were reviewed by 42 pulmonary pathologists first according to the WHO classification and after tutorial according to a modified classification. A third round was conducted based on feedback from 41 peers of previous rounds. Additionally, orthogonal biomarker analysis was performed.

RESULTS

In the first two rounds, 42 pathologists from 13 countries assessed all 70 cases, while 36 pathologists evaluated 41 non-unanimous cases in the third round. Kappa values for invasiveness increased in rounds 1, 2, and 3 to 0.27, 0.45 and 0.62, respectively. In contrast to low variation in total tumor size measurements (6 %), a marked increase in invasive tumor size variation was observed (42 %), which was associated with high uncertainty. In the third round 10 cases were non-invasive, all without recurrence. The modified classification showed in the 3rd round marked reduction of the variation in pT staging compared to the current WHO classification. Proliferation rate, tumor mutational burden, and transcriptomic profiles supported the distinction between invasive cases and non-invasive cases of the modified classification.

CONCLUSION

The modified classification demonstrates essentially higher reproducibility compared to the current WHO classification in NMA. The modified classification proves valuable in identifying low-risk lesions that are entirely non-invasive, and is supported by biomarker analysis.

Normalization of gene counts affects principal components-based exploratory analysis of RNA-sequencing data

Normalization of gene expression count data is an essential step of in the analysis of RNA-sequencing data. Its statistical analysis has been mostly addressed in the context of differential expression analysis, that is in the univariate setting. However, relationships among genes and samples are better explored and quantified using multivariate exploratory data analysis tools like Principal Component Analysis (PCA). In this study we investigate how normalization impacts the PCA model and its interpretation, considering twelve different widely used normalization methods that were applied on simulated and experimental data. Correlation patterns in the normalized data were explored using both summary statistics and Covariance Simultaneous Component Analysis. The impact of normalization on the PCA solution was assessed by exploring the model complexity, the quality of sample clustering in the low-dimensional PCA space and gene ranking in the model fit to normalized data. PCA models upon normalization were interpreted in the context gene enrichment pathway analysis. We found that although PCA score plots are often similar independently form the normalization used, biological interpretation of the models can depend heavily on the normalization method applied.

A genome assembly and transcriptome atlas of the inbred Babraham pig to illuminate porcine immunogenetic variation

The inbred Babraham pig serves as a valuable biomedical model for research due to its high level of homozygosity, including in the major histocompatibility complex (MHC) loci and likely other important immune-related gene complexes, which are generally highly diverse in outbred populations. As the ability to control for this diversity using inbred organisms is of great utility, we sought to improve this resource by generating a long-read whole genome assembly and transcriptome atlas of a Babraham pig. The genome was de novo assembled using PacBio long reads and error-corrected using Illumina short reads. Assembled contigs were then mapped to the porcine reference assembly, Sscrofa11.1, to generate chromosome-level scaffolds. The resulting TPI_Babraham_pig_v1 assembly is nearly as contiguous as Sscrofa11.1 with a contig N50 of 34.95 Mb and contig L50 of 23. The remaining sequence gaps are generally the result of poor assembly across large and highly repetitive regions such as the centromeres and tandemly duplicated gene families, including immune-related gene complexes, that often vary in gene content between haplotypes. We also further confirm homozygosity across the Babraham MHC and characterize the allele content and tissue expression of several other immune-related gene complexes, including the antibody and T cell receptor loci, the natural killer complex, and the leukocyte receptor complex. The Babraham pig genome assembly provides an alternate highly contiguous porcine genome assembly as a resource for the livestock genomics community. The assembly will also aid biomedical and veterinary research that utilizes this animal model such as when controlling for genetic variation is critical.

Rhamnolipid-Enriched PA3 Fraction from Pseudomonas aeruginosa SWUC02 Primes Chili Plant Defense Against Anthracnose

Chili anthracnose, caused by Colletotrichum truncatum, causes significant yield loss in chili production. In this study, we investigated the elicitor properties of a rhamnolipid (RL)-enriched PA3 fraction derived from Pseudomonas aeruginosa SWUC02 in inducing systemic resistance in yellow chili seedlings and antifungal activity against C. truncatum CFPL01 (Col). Fractionation of the ethyl acetate extract yielded 12 fractions, with PA3 demonstrating the most effective disease suppression, reducing the disease severity index to 4 ± 7.35% at 7 days post-inoculation compared with Col inoculation alone (83 ± 23.57%). PA3 also exhibited direct antifungal activity, inhibiting Col mycelial growth by 41 ± 0.96% at 200 µg/mL. Subfractionation revealed PA3 as a mixture of mono- and di-RLs, confirmed by 1H nuclear magnetic resonance and electrospray ionization mass spectrometry data. Additionally, PA3 enhanced seed germination and promoted plant growth without causing phytotoxicity. Transcriptomics revealed that PA3 pre-treatment prior to Col infection primed the defense response, upregulating defense-related genes involved in the phenylpropanoid, flavonoid, and jasmonic acid biosynthesis pathways, as well as those associated with cell wall reinforcement. Our findings highlight the potential of RL-enriched PA3 as both an antifungal agent and a plant defense elicitor, with transcriptome data providing new insights into defense priming and resistance pathways in chili, offering an eco-friendly solution for sustainable anthracnose management.

Time-Resolved Multiomics Illustrates Host and Gut Microbe Interactions during Salmonella Infection

Salmonella infection, also known as Salmonellosis, is one of the most common food-borne illnesses. Salmonella infection can trigger host defensive functions, including an inflammatory response. The provoked-host inflammatory response has a significant impact on the bacterial population in the gut. In addition, Salmonella competes with other gut microorganisms for survival and growth within the host. Compositional and functional alterations in gut bacteria occur because of the host immunological response and competition between Salmonella and the gut microbiome. Host variation and the inherent complexity of the gut microbial community make understanding commensal and pathogen interactions particularly difficult during a Salmonella infection. Here, we present metabolomics and lipidomics analyses along with the 16S rRNA sequence analysis, revealing a comprehensive view of the metabolic interactions between the host and gut microbiota during Salmonella infection in a CBA/J mouse model. We found that different metabolic pathways were altered over the four investigated time points of Salmonella infection (days -2, +2, +6, and +13). Furthermore, metatranscriptomics analysis integrated with metabolomics and lipidomics analysis facilitated an understanding of the heterogeneous response of mice, depending on the degree of dysbiosis.

Extracellular matrix modulates depot-specific adipogenic capacity in adipose tissue of dairy cattle

Adipose tissue (AT) expands through both hyperplasia and hypertrophy. During adipogenesis, adipose stromal and progenitor cells (ASPC) proliferate and then accumulate lipids, influenced by the local AT microenvironment. Increased adipogenic capacity is desirable as it relates to metabolic health, especially in transition dairy cows where excess free fatty acids in circulation can compromise metabolic and immune health. Our aim was to elucidate the depot-specific adipogenic capacity and extracellular matrix (EMX) properties of subcutaneous (SAT) and visceral (VAT) AT of dairy cows and define how the EMX affects adipogenesis. Flank SAT and omental VAT samples were collected from dairy cows in a local abattoir. Tissue samples were used for transcriptome analysis, targeted real-time quantitative PCR (RT-qPCR) for adipogenic markers, adipocyte sizing, assessment of viscoelastic properties and collagen accumulation, and then decellularized for native EMX isolation. For in vitro analyses, SAT and VAT samples were digested via collagenase, and ASPC cultured for metabolic analysis. Adipogenic capacity was assessed by adipocyte size, quantification of ASPC in stromal vascular fraction (SVF) via flow cytometry, and gene expression of adipogenic markers. In addition, functional assays including lipolysis and glucose uptake were performed to further characterize SAT and VAT adipocyte metabolic function. Data were analyzed using SAS (version 9.4; SAS Institute Inc., Cary, NC) and GraphPad Prism 9. Subcutaneous AT adipogenic capacity was greater than VAT's, as indicated by increased ASPC abundance, increased magnitude of adipocyte ADIPOQ and FASN expression during differentiation, and higher adipocyte lipid accumulation as shown by an increased proportion of larger adipocytes and abundance of lipid droplets. Rheologic analysis revealed that VAT is stiffer than SAT, which led us to hypothesize that differences between SAT and VAT adipogenic capacity were partly mediated by depot-specific EMX microenvironment. Thus, we studied depot-specific EMX-adipocyte crosstalk using a 3-dimensional model with native EMX (decellularized AT). Subcutaneous AT and VAT ASPC were cultured and differentiated into adipocytes within depot-matched and mismatched EMX for 14 d, followed by ADIPOQ expression analysis. Visceral AT EMX impaired ADIPOQ expression in SAT cells. Our results demonstrate that SAT is more adipogenic than VAT and suggest that divergences between SAT and VAT adipogenesis are partially mediated by the depot-specific EMX microenvironment.

Time-resolved multi-omics reveals diverse metabolic strategies of Salmonella during diet-induced inflammation

With a rise in antibiotic resistance and chronic infection, the metabolic response of Salmonella enterica serovar Typhimurium to various dietary conditions over time remains an understudied avenue for novel, targeted therapeutics. Elucidating how enteric pathogens respond to dietary variation not only helps us decipher the metabolic strategies leveraged for expansion but also assists in proposing targets for therapeutic interventions. In this study, we use a multi-omics approach to identify the metabolic response of Salmonella enterica serovar Typhimurium in mice on both a fibrous diet and high-fat diet over time. When comparing Salmonella gene expression between diets, we found a preferential use of respiratory electron acceptors consistent with increased inflammation in high-fat diet mice. Looking at the high-fat diet over the course of infection, we noticed heterogeneity in samples based on Salmonella ribosomal activity, which is separated into three infection phases: early, peak, and late. We identified key respiratory, carbon, and pathogenesis gene expressions descriptive of each phase. Surprisingly, we identified genes associated with host cell entry expressed throughout infection, suggesting subpopulations of Salmonella or stress-induced dysregulation. Collectively, these results highlight not only the sensitivity of Salmonella to its environment but also identify phase-specific genes that may be used as therapeutic targets to reduce infection.IMPORTANCEIdentifying novel therapeutic strategies for Salmonella infection that occur in relevant diets and over time is needed with the rise of antibiotic resistance and global shifts toward Western diets that are high in fat and low in fiber. Mice on a high-fat diet are more inflamed compared to those on a fibrous diet, creating an environment that results in more favorable energy generation for Salmonella. We observed differential gene expression across infection phases in mice over time on a high-fat diet. Together, these findings reveal the metabolic tuning of Salmonella to dietary and temporal perturbations. Research like this, which explores the dimensions of pathogen metabolic plasticity, can pave the way for rationally designed strategies to control disease.

A benchmark of RNA-seq data normalization methods for transcriptome mapping on human genome-scale metabolic networks

Genome-scale metabolic models (GEMs) cover the entire list of metabolic genes in an organism and associated reactions, in a tissue/condition non-specific manner. RNA-seq provides crucial information to make the GEMs condition-specific. Integrative Metabolic Analysis Tool (iMAT) and Integrative Network Inference for Tissues (INIT) are the two most popular algorithms to create condition-specific GEMs from human transcriptome data. The normalization method of choice for raw RNA-seq count data affects the model content produced by these algorithms and their predictive accuracy. However, a benchmark of the RNA-seq normalization methods on the performance of iMAT and INIT algorithms is missing in the literature. Another important phenomenon is covariates such as age and gender in a dataset, and they can affect the predictivity of analysis. In this study, we aimed to compare five different RNA-seq data normalization methods (TPM, FPKM, TMM, GeTMM, and RLE) and covariate adjusted versions of the normalized data by mapping them on a human GEM using the iMAT and INIT algorithms to generate personalized metabolic models. We used RNA-seq data for Alzheimer's disease (AD) and lung adenocarcinoma (LUAD) patients. The results demonstrated that RNA-seq data normalized by the RLE, TMM, or GeTMM methods enabled the production of condition-specific metabolic models with considerably low variability in terms of the number of active reactions compared to the within-sample normalization methods (FPKM, TPM). Using these models, we could more accurately capture the disease-associated genes (average accuracy of ~0.80 for AD and ~0.67 for LUAD) for the RLE, TMM, and GeTMM normalization methods. An increase in the accuracies was observed for all the methods when covariate adjustment was applied. We found a similar accuracy trend when we compared the metabolites of perturbed reactions to metabolome data for AD. Together, our benchmark study shows that the between-sample RNA-seq normalization methods reduce false positive predictions at the expense of missing some true positive genes when mapped on GEMs.

A germline PAF1 paralog complex ensures cell type-specific gene expression

Animal germline development and fertility rely on paralogs of general transcription factors that recruit RNA polymerase II to ensure cell type-specific gene expression. It remains unclear whether gene expression processes downstream from such paralog-based transcription is distinct from that of canonical RNA polymerase II genes. In Drosophila, the testis-specific TBP-associated factors (tTAFs) activate over a thousand spermatocyte-specific gene promoters to enable meiosis and germ cell differentiation. Here, we show that efficient termination of tTAF-activated transcription relies on testis-specific paralogs of canonical polymerase-associated factor 1 complex (PAF1C) proteins, which form a testis-specific PAF1C (tPAF). Consequently, tPAF mutants show aberrant expression of hundreds of downstream genes due to read-in transcription. Furthermore, tPAF facilitates expression of Y-linked male fertility factor genes and thus serves to maintain spermatocyte-specific gene expression. Consistently, tPAF is required for the segregation of meiotic chromosomes and male fertility. Supported by comparative in vivo protein interaction assays, we provide a mechanistic model for the functional divergence of tPAF and the PAF1C and identify transcription termination as a developmentally regulated process required for germline-specific gene expression.

The fatty acid omega hydroxylase genes (CYP4 family) in the progression of metabolic dysfunction-associated steatotic liver disease (MASLD): An RNA sequence database analysis and review

Fatty acid omega hydroxylase P450s consist of enzymes that hydroxylate various chain-length saturated and unsaturated fatty acids (FAs) and bioactive eicosanoid lipids. The human cytochrome P450 gene 4 family (CYP4) consists of 12 members that are associated with several human diseases. However, their role in the progression of metabolic dysfunction-associated fatty liver disease (MASLD) remains largely unknown. It has long been thought that the induction of CYP4 family P450 during fasting and starvation prevents FA-related lipotoxicity through FA metabolism to dicarboxylic acids that are chain-shortened in peroxisomes and then transported to the mitochondria for complete oxidation. Several studies have revealed that peroxisome succinate transported to the mitochondria is used for gluconeogenesis during fasting and starvation, and recent evidence suggests that peroxisome acetate can be utilized for lipogenesis and lipid droplet formation as well as epigenetic modification of gene transcription. In addition, omega hydroxylation of the bioactive eicosanoid arachidonic acid to 20-Hydroxyeicosatetraenoic acid (20-HETE) is essential for activating the GPR75 receptor, leading to vasoconstriction and cell proliferation. Several mouse models of diet-induced MASLD have revealed the induction of selective CYP4A members and the suppression of CYP4F during steatosis and steatohepatitis, suggesting a critical metabolic role in the progression of fatty liver disease. Thus, to further investigate the functional roles of CYP4 genes, we analyzed the differential gene expression of 12 members of CYP4 gene family in datasets from the Gene Expression Omnibus (GEO) from patients with steatosis, steatohepatitis, fibrosis, cirrhosis, and hepatocellular carcinoma. We also observed the differential expression of various CYP4 genes in the progression of MASLD, indicating that different CYP4 members may have unique functional roles in the metabolism of specific FAs and eicosanoids at various stages of fatty liver disease. These results suggest that targeting selective members of the CYP4A family is a viable therapeutic approach for treating and managing MASLD.

Deciphering Antibiotic-Targeted Metabolic Pathways in Acinetobacter baumannii: Insights from Transcriptomics and Genome-Scale Metabolic Modeling

In the ongoing battle against antibiotic-resistant infections, Acinetobacter baumannii has emerged as a critical pathogen in healthcare settings. To understand its response to antibiotic-induced stress, we integrated transcriptomic data from various antibiotics (amikacin sulfate, ciprofloxacin, polymyxin-B, and meropenem) with metabolic modeling techniques. Key metabolic pathways, including arginine and proline metabolism, glycine-serine and threonine metabolism, glyoxylate and dicarboxylate metabolism, and propanoate metabolism, were significantly impacted by all four antibiotics across multiple strains. Specifically, biotin metabolism was consistently down-regulated under polymyxin-B treatment, while fatty acid metabolism was perturbed under amikacin sulfate. Ciprofloxacin induced up-regulation in glycerophospholipid metabolism. Validation with an independent dataset focusing on colistin treatment confirmed alterations in fatty acid degradation, elongation, and arginine metabolism. By harmonizing genetic data with metabolic modeling and a metabolite-centric approach, our findings offer insights into the intricate adaptations of A. baumannii under antibiotic pressure, suggesting more effective strategies to combat antibiotic-resistant infections.

Limosilactobacillus reuteri promotes the expression and secretion of enteroendocrine- and enterocyte-derived hormones

Observations that intestinal microbes can beneficially impact host physiology have prompted investigations into the therapeutic usage of such microbes in a range of diseases. For example, the human intestinal microbe Limosilactobacillus reuteri strains ATCC PTA 6475 and DSM 17938 are being considered for use for intestinal ailments including colic, infection, and inflammation as well as non-intestinal ailments including osteoporosis, wound healing, and autism spectrum disorder. While many of their beneficial properties are attributed to suppressing inflammatory responses in the gut, we postulated that L. reuteri may also regulate hormones of the gastrointestinal tract to affect physiology within and outside of the gut. To determine if L. reuteri secreted factors impact the secretion of enteric hormones, we treated an engineered jejunal organoid line, NGN3-HIO, which can be induced to be enriched in enteroendocrine cells, with L. reuteri 6475 or 17938 conditioned medium and performed transcriptomics. Our data suggest that these L. reuteri strains affect the transcription of many gut hormones, including vasopressin and luteinizing hormone subunit beta, which have not been previously recognized as being produced in the gut epithelium. Moreover, we find that these hormones appear to be produced in enterocytes, in contrast to canonical gut hormones which are produced in enteroendocrine cells. Finally, we show that L. reuteri conditioned media promotes the secretion of several enteric hormones including serotonin, GIP, PYY, vasopressin, and luteinizing hormone subunit beta. These results support L. reuteri affecting host physiology through intestinal hormone secretion, thereby expanding our understanding of the mechanistic actions of this microbe.

Comparative genomics illuminates karyotype and sex chromosome evolution of sharks

Chondrichthyes is an important lineage to reconstruct the evolutionary history of vertebrates. Here, we analyzed genome synteny for six chondrichthyan chromosome-level genomes. Our comparative analysis reveals a slow evolutionary rate of chromosomal changes, with infrequent but independent fusions observed in sharks, skates, and chimaeras. The chondrichthyan common ancestor had a proto-vertebrate-like karyotype, including the presence of 18 microchromosome pairs. The X chromosome is a conversed microchromosome shared by all sharks, suggesting a likely common origin of the sex chromosome at least 181 million years ago. We characterized the Y chromosomes of two sharks that are highly differentiated from the X except for a small young evolutionary stratum and a small pseudoautosomal region. We found that shark sex chromosomes lack global dosage compensation but that dosage-sensitive genes are locally compensated. Our study on shark chromosome evolution enhances our understanding of shark sex chromosomes and vertebrate chromosome evolution.

Multi-omic analysis of bat versus human fibroblasts reveals altered central metabolism

Bats have unique characteristics compared to other mammals, including increased longevity and higher resistance to cancer and infectious disease. While previous studies have analyzed the metabolic requirements for flight, it is still unclear how bat metabolism supports these unique features, and no study has integrated metabolomics, transcriptomics, and proteomics to characterize bat metabolism. In this work, we performed a multi-omics data analysis using a computational model of metabolic fluxes to identify fundamental differences in central metabolism between primary lung fibroblast cell lines from the black flying fox fruit bat (Pteropus alecto) and human. Bat cells showed higher expression levels of Complex I components of electron transport chain (ETC), but, remarkably, a lower rate of oxygen consumption. Computational modeling interpreted these results as indicating that Complex II activity may be low or reversed, similar to an ischemic state. An ischemic-like state of bats was also supported by decreased levels of central metabolites and increased ratios of succinate to fumarate in bat cells. Ischemic states tend to produce reactive oxygen species (ROS), which would be incompatible with the longevity of bats. However, bat cells had higher antioxidant reservoirs (higher total glutathione and higher ratio of NADPH to NADP) despite higher mitochondrial ROS levels. In addition, bat cells were more resistant to glucose deprivation and had increased resistance to ferroptosis, one of the characteristics of which is oxidative stress. Thus, our studies revealed distinct differences in the ETC regulation and metabolic stress responses between human and bat cells.

Rank-In Integrated Machine Learning and Bioinformatic Analysis Identified the Key Genes in HFPO-DA (GenX) Exposure to Human, Mouse, and Rat Organisms

Hexafluoropropylene Oxide Dimer Acid (HFPO-DA or GenX) is a pervasive perfluorinated compound with scant understood toxic effects. Toxicological studies on GenX have been conducted using animal models. To research deeper into the potential toxicity of GenX in humans and animals, we undertook a comprehensive analysis of transcriptome datasets across different species. A rank-in approach was utilized to merge different transcriptome datasets, and machine learning algorithms were employed to identify key genetic mechanisms common among various species and humans. We identified seven genes-TTR, ATP6V1B1, EPHX1, ITIH3, ATXN10, UBXN1, and HPX-as potential variables for classification of GenX-exposed samples, and the seven genes were verified in separate datasets of human, mouse, and rat samples. Bioinformatic analysis of the gene dataset further revealed that mitochondrial function and metabolic processes may be modulated by GenX through these key genes. Our findings provide insights into the underlying genetic mechanisms and toxicological impacts of GenX exposure across different species and offer valuable references for future studies using animal models to examine human exposure to GenX.

Differentially expressed heterogeneous overdispersion genes testing for count data

The mRNA-seq data analysis is a powerful technology for inferring information from biological systems of interest. Specifically, the sequenced RNA fragments are aligned with genomic reference sequences, and we count the number of sequence fragments corresponding to each gene for each condition. A gene is identified as differentially expressed (DE) if the difference in its count numbers between conditions is statistically significant. Several statistical analysis methods have been developed to detect DE genes based on RNA-seq data. However, the existing methods could suffer decreasing power to identify DE genes arising from overdispersion and limited sample size, where overdispersion refers to the empirical phenomenon that the variance of read counts is larger than the mean of read counts. We propose a new differential expression analysis procedure: heterogeneous overdispersion genes testing (DEHOGT) based on heterogeneous overdispersion modeling and a post-hoc inference procedure. DEHOGT integrates sample information from all conditions and provides a more flexible and adaptive overdispersion modeling for the RNA-seq read count. DEHOGT adopts a gene-wise estimation scheme to enhance the detection power of differentially expressed genes when the number of replicates is limited as long as the number of conditions is large. DEHOGT is tested on the synthetic RNA-seq read count data and outperforms two popular existing methods, DESeq2 and EdgeR, in detecting DE genes. We apply the proposed method to a test dataset using RNAseq data from microglial cells. DEHOGT tends to detect more differently expressed genes potentially related to microglial cells under different stress hormones treatments.

Species-specific duplicated FMRFaR-like gene A62 regulates spontaneous locomotion in Apolygus lucorum

BACKGROUND

Apolygus lucorum, a major cotton pest, has undergone a significant expansion of the FMRFaR gene within the GPCR superfamily, resulting in two classes of GPCR, namely FMRFaR (A54-55) and newly duplicated FMRFaR-like (A56-62). Notably, FMRFaR-like genes, particularly A62, show enhanced expression in the legs and wings of adults, indicating their potential role in locomotion. Employing A62 as a representative of FMRFaR-like, our study investigates the influence of FMRFa, FMRFaR, and FMRFaR-like on locomotion and development of A. lucorum.

RESULTS

FMRFaR and FMRFa exhibit comparable temporal and tissue expression patterns, whereas the FMRFaR-like genes within A. lucorum exhibit completely distinct evolutionary and expression patterns compared to classical FMRFaR. RNA interference (RNAi) experiments revealed that suppressing FMRFa expression results in complete lethality in A. lucorum, but neither FMRFaR nor A62 exhibit the same effect after RNAi. Suppressing the expression of FMRFa only decreases the expression of the A54 gene simultaneously, suggesting that A54 may function as a classical FMRFaR activated by FMRFa. RNAi of A62 leads to wing malformation and a significant reduction in spontaneous movement behavior in A. lucorum. Further transcriptomic analysis revealed that A62 affects the A. lucorum's movement behavior through energy metabolism pathways and motor protein pathways.

CONCLUSION

Our study unveils the unique and complex roles of FMRFa and its receptor in A. lucorum. These findings provide valuable insights into potential targets for pest control strategies aimed at managing A. lucorum populations in cotton fields. © 2024 Society of Chemical Industry.

Early life adversity is associated with differential gene expression in immune cells: A cluster-based analysis across an acute psychosocial stressor

Elucidating mechanisms by which early-life adversity (ELA) contributes to increased disease risk is important for mitigating adverse health outcomes. Prior work has found differences in immune cell gene expression related to inflammation and mitochondrial activity. Using a within-person between-group experimental design, we investigated differences in gene expression clusters across acute psychosocial stress and no-stress conditions. Participants were young adults (N = 29, aged 18 - 25 years, 62 % female, 47 % with a history of ELA). Gene expression was assessed in peripheral blood mononuclear cells collected at 8 blood draws spanning two 5-hour sessions (stress vs. no-stress) separated by a week, 4 across each session (number of observations = 221). We applied two unsupervised gene clustering methods - latent profile analysis (LPA) and weighted gene co-expression analysis (WGCNA) - to cluster genes with similar expression patterns across participants. LPA identified 11 clusters, 7 of which were significantly associated with ELA-status. WGCNA identified 5 clusters, 3 of which were significantly associated with ELA-status. LPA- and WGCNA-identified clusters were correlated, and all clusters were highly preserved across sessions and time. There was no significant effect of acute stress on cluster gene expression, but there was a significant effect of time, and significant differences by ELA-status. ELA-associated clusters related to RNA splicing/processing, inflammation, leukocyte differentiation and division, and mitochondrial activity were differentially expressed across time: ELA-exposed individuals showed decreased expression of these clusters at 90-minutes while controls showed increased expression. Our findings replicate previous work in this area and highlight additional mechanisms by which ELA may contribute to disease risk.

Microbial polyphenol metabolism is part of the thawing permafrost carbon cycle

With rising global temperatures, permafrost carbon stores are vulnerable to microbial degradation. The enzyme latch theory states that polyphenols should accumulate in saturated peatlands due to diminished phenol oxidase activity, inhibiting resident microbes and promoting carbon stabilization. Pairing microbiome and geochemical measurements along a permafrost thaw-induced saturation gradient in Stordalen Mire, a model Arctic peatland, we confirmed a negative relationship between phenol oxidase expression and saturation but failed to support other trends predicted by the enzyme latch. To inventory alternative polyphenol removal strategies, we built CAMPER, a gene annotation tool leveraging polyphenol enzyme knowledge gleaned across microbial ecosystems. Applying CAMPER to genome-resolved metatranscriptomes, we identified genes for diverse polyphenol-active enzymes expressed by various microbial lineages under a range of redox conditions. This shifts the paradigm that polyphenols stabilize carbon in saturated soils and highlights the need to consider both oxic and anoxic polyphenol metabolisms to understand carbon cycling in changing ecosystems.

Comparative transcriptome and methylome of polar bears, giant and red pandas reveal diet-driven adaptive evolution

Epigenetic regulation plays an important role in the evolution of species adaptations, yet little information is available on the epigenetic mechanisms underlying the adaptive evolution of bamboo-eating in both giant pandas (Ailuropoda melanoleuca) and red pandas (Ailurus fulgens). To investigate the potential contribution of epigenetic to the adaptive evolution of bamboo-eating in giant and red pandas, we performed hepatic comparative transcriptome and methylome analyses between bamboo-eating pandas and carnivorous polar bears (Ursus maritimus). We found that genes involved in carbohydrate, lipid, amino acid, and protein metabolism showed significant differences in methylation and expression levels between the two panda species and polar bears. Clustering analysis of gene expression revealed that giant pandas did not form a sister group with the more closely related polar bears, suggesting that the expression pattern of genes in livers of giant pandas and red pandas have evolved convergently driven by their similar diets. Compared to polar bears, some key genes involved in carbohydrate metabolism and biological oxidation and cholesterol synthesis showed hypomethylation and higher expression in giant and red pandas, while genes involved in fat digestion and absorption, fatty acid metabolism, lysine degradation, resistance to lipid peroxidation and detoxification showed hypermethylation and low expression. Our study elucidates the special nutrient utilization mechanism of giant pandas and red pandas and provides some insights into the molecular mechanism of their adaptive evolution of bamboo feeding. This has important implications for the breeding and conservation of giant pandas and red pandas.

EPI-X4, a CXCR4 antagonist inhibits tumor growth in pancreatic cancer and lymphoma models

Endogenous peptide inhibitor for CXCR4 (EPI-X4) is a CXCR4 antagonist with potential for cancer therapy. It is a processed fragment of serum albumin from the hemofiltrate of dialysis patients. This study reports the efficacy of fifteen EPI-X4 derivatives in pancreatic cancer and lymphoma models. In vitro, the peptides were investigated for antiproliferation (cytotoxicity) by MTT assay. The mRNA expression for CXCR4 and CXCL12 was determined by RT-PCR, chip array and RNA sequencing. Chip array analysis yielded 634 genes associated with CXCR4/CXCL12 signaling. About 21% of these genes correlated with metastasis in the context of cell motility, proliferation, and survival. Expression levels of these genes were altered in pancreatic cancer (36%), lymphoma models (53%) and in patients' data (58%). EPI-X4 derivatives failed to inhibit cell proliferation due to low expression of CXCR4 in vitro, but inhibited tumor growth in the bioassays with significant efficacy. In the pancreatic cancer model, EPI-X4a, f and k inhibited mean tumor growth by > 50% and even caused complete remissions. In the lymphoma model, EPI-X4b, n and p inhibited mean tumor growth by > 70% and caused stable disease. Given the non-toxic and non-immunogenic properties of EPI-X4, these findings underscore its status as a promising therapy of pancreatic cancer and lymphoma and warrant further studies. SIMPLE SUMMARY: This study examined the value of chemokine receptor CXCR4 as an antineoplastic target for the endogenous peptide inhibitor of CXCR4 (EPI-X4), a 12-meric peptide derived from serum albumin. EPI-X4 inhibits CXCR4 interaction with its natural ligand, CXCL12 (SDF1). Therefore, malignancies (including pancreatic cancer and lymphoma) that depend on the CXCR4/CXCL12 pathway for progression can be targeted with EPI-X4. Of 634 genes that were linked to the CXCR4/CXCL12 pathway, 21% were associated with metastasis. In cultured human Suit2-007 pancreatic cancer cells, CXCR4 showed low to undetectable expression, which was why EPI-X4 did not inhibit pancreatic cancer cell proliferation. These findings were different in vivo, where CXCR4 was highly expressed and EPI-X4 inhibited tumor growth in rodents harboring pancreatic cancer or lymphoma. In the pancreatic cancer model, EPI-X4 derivatives a, f and k caused complete remissions, while in lymphomas EPI-X4 derivatives b, n and p caused stable disease.

Stable feature selection utilizing Graph Convolutional Neural Network and Layer-wise Relevance Propagation for biomarker discovery in breast cancer

High-throughput technologies are becoming increasingly important in discovering prognostic biomarkers and in identifying novel drug targets. With Mammaprint, Oncotype DX, and many other prognostic molecular signatures breast cancer is one of the paradigmatic examples of the utility of high-throughput data to deliver prognostic biomarkers, that can be represented in a form of a rather short gene list. Such gene lists can be obtained as a set of features (genes) that are important for the decisions of a Machine Learning (ML) method applied to high-dimensional gene expression data. Several studies have identified predictive gene lists for patient prognosis in breast cancer, but these lists are unstable and have only a few genes in common. Instability of feature selection impedes biological interpretability: genes that are relevant for cancer pathology should be members of any predictive gene list obtained for the same clinical type of patients. Stability and interpretability of selected features can be improved by including information on molecular networks in ML methods. Graph Convolutional Neural Network (GCNN) is a contemporary deep learning approach applicable to gene expression data structured by a prior knowledge molecular network. Layer-wise Relevance Propagation (LRP) and SHapley Additive exPlanations (SHAP) are methods to explain individual decisions of deep learning models. We used both GCNN+LRP and GCNN+SHAP techniques to construct feature sets by aggregating individual explanations. We suggest a methodology to systematically and quantitatively analyze the stability, the impact on the classification performance, and the interpretability of the selected feature sets. We used this methodology to compare GCNN+LRP to GCNN+SHAP and to more classical ML-based feature selection approaches. Utilizing a large breast cancer gene expression dataset we show that, while feature selection with SHAP is useful in applications where selected features have to be impactful for classification performance, among all studied methods GCNN+LRP delivers the most stable (reproducible) and interpretable gene lists.

Near-gapless genome and transcriptome analyses provide insights into fruiting body development in Lentinula edodes

Fruiting body development in macrofungi is an intensive research subject. In this study, high-quality genomes were assembled for two sexually compatible monokaryons from a heterokaryotic Lentinula edodes strain WX1, and variations in L. edodes genomes were analyzed. Specifically, differential gene expression and allele-specific expression (ASE) were analyzed using the two monokaryotic genomes and transcriptome data from four different stages of fruiting body development in WX1. Results revealed that after aeration, mycelia sensed cell wall stress, pheromones, and a decrease in CO2 concentration, leading to up-regulated expression in genes related to cell adhesion, cell wall remodeling, proteolysis, and lipid metabolism, which may promote primordium differentiation. Aquaporin genes and those related to proteolysis, mitosis, lipid, and carbohydrate metabolism may play important roles in primordium development, while genes related to tissue differentiation and sexual reproduction were active in fruiting body. Several essential genes for fruiting body development were allele-specifically expressed and the two nuclear types could synergistically regulate fruiting body development by dominantly expressing genes with different functions. ASE was probably induced by long terminal repeat-retrotransposons. Findings here contribute to the further understanding of the mechanism of fruiting body development in macrofungi.

Identification of unique genomic signatures in patients with fibromyalgia and chronic pain

Fibromyalgia (FM) is a chronic pain syndrome characterized by widespread pain. The pathophysiology of fibromyalgia is not clearly understood and there are no specific biomarkers available for accurate diagnosis. Here we define genomic signatures using high throughput RNA sequencing on 96 fibromyalgia and 93 control cases. Our findings revealed three major fibromyalgia-associated expression signatures. The first group included 43 patients with a signature enriched for gene expression associated with extracellular matrix and downregulation of RhoGDI signaling pathway. The second group included 30 patients and showed a profound reduction in the expression of inflammatory mediators with an increased expression of genes involved in the CLEAR signaling pathway. These results suggest defective tissue homeostasis associated with the extra-cellular matrix and cellular program that regulates lysosomal biogenesis and participates in macromolecule clearance in fibromyalgia. The third group of 17 FM patients showed overexpression of pathways that control acute inflammation and dysfunction of the global transcriptional process. The result of this study indicates that FM is a heterogeneous and complex disease. Further elucidation of these pathways will lead to the development of accurate diagnostic markers, and effective therapeutic options for fibromyalgia.

The transcriptomic signature of adaptations associated with perfume collection in orchid bees

Secondary sexual traits can convey information on mate quality with the signal honesty maintained by the costly nature of trait expression. Mating signals are also often underpinned by physiological, morphological, and behavioural adaptations, which may require the evolution of novelty, but the genetic basis in many cases is unknown. In orchid bees, males acquire chemical compounds from the environment that act as pheromone-like bouquets (perfumes) during courtship displays. This process could be costly, potentially due to the cognitive demands of learning and the physiological demands of collecting a mix of extrinsic chemical compounds that may require detoxification. Furthermore, a novel trait, a specialized perfume pouch in the hind leg, is required for compound storage. We studied gene expression in the brain, hind leg, and Malpighian tubules-a tissue involved in detoxification-to investigate changes in gene expression following perfume collection. We detected upregulation of genes enriched in functions related to transcription, odorant binding, and receptor activity in the Malpighian tubules. On the other hand, we did not find any evidence for learning processes following perfume collection, or gene expression changes in the hind leg, perhaps due to constitutive expression, or the age of the sampled bees. We did identify high expression of chemosensory proteins in the hind legs, which we suggest could play a role in perfume collection or storage, with further functional studies necessary to determine their binding properties and potential physiological importance. Los rasgos sexuales secundarios pueden servir como indicadores de calidad de la pareja, y en algunos casos la honestidad de la señal se mantiene por el costo de expresar el rasgo. A menudo las señales sexuales están respaldadas por adaptaciones fisiológicas, morfológicas y de comportamiento por lo tanto pueden requerir la evolución de nuevos rasgos, pero en muchos casos se desconoce la base genética. En las abejas de las orquídeas, los machos recolectan compuestos químicos del medio ambiente, los cuales actúan como feromonas (perfumes) durante el despliegue de cortejo. Este proceso podría ser costoso, posiblemente debido a las demandas cognitivas del aprendizaje y las demandas fisiológicas de recolectar una mezcla de compuestos químicos extrínsecos que pueden requerir desintoxicación. Además, se requiere la evolución de un contenedor para almacenar perfumes en la pata trasera. Para investigar los cambios en la expresión génica después de la recolección de perfume, estudiamos la expresión génica en el cerebro, la pata trasera y los túbulos de Malpighi (tejido involucrado en la desintoxicación). Encontramos varios genes regulados positivamente en los túbulos de Malpighi después de la recolección que están enriquecidos en factores de transcripción, proteínas de fijación de olores, y proteínas con actividad de receptor. Por otro lado, no encontramos ninguna evidencia de procesos de aprendizaje posteriores a la recolección de perfumes, o cambios en la expresión génica en la pata trasera, esto quizás debido a la expresión constitutiva o la edad de las abejas muestreadas. Además, identificamos una alta expresión de proteínas quimio-sensoriales en las patas traseras, que podría desempeñar un papel en la recolección o almacenamiento de perfumes. Más estudios funcionales son necesarios para determinar las propiedades de fijación de las proteínas y su potencial importancia fisiológica.

Methylotrophy in the Mire: direct and indirect routes for methane production in thawing permafrost

While wetlands are major sources of biogenic methane (CH4), our understanding of resident microbial metabolism is incomplete, which compromises the prediction of CH4 emissions under ongoing climate change. Here, we employed genome-resolved multi-omics to expand our understanding of methanogenesis in the thawing permafrost peatland of Stordalen Mire in Arctic Sweden. In quadrupling the genomic representation of the site's methanogens and examining their encoded metabolism, we revealed that nearly 20% of the metagenome-assembled genomes (MAGs) encoded the potential for methylotrophic methanogenesis. Further, 27% of the transcriptionally active methanogens expressed methylotrophic genes; for Methanosarcinales and Methanobacteriales MAGs, these data indicated the use of methylated oxygen compounds (e.g., methanol), while for Methanomassiliicoccales, they primarily implicated methyl sulfides and methylamines. In addition to methanogenic methylotrophy, >1,700 bacterial MAGs across 19 phyla encoded anaerobic methylotrophic potential, with expression across 12 phyla. Metabolomic analyses revealed the presence of diverse methylated compounds in the Mire, including some known methylotrophic substrates. Active methylotrophy was observed across all stages of a permafrost thaw gradient in Stordalen, with the most frozen non-methanogenic palsa found to host bacterial methylotrophy and the partially thawed bog and fully thawed fen seen to house both methanogenic and bacterial methylotrophic activities. Methanogenesis across increasing permafrost thaw is thus revised from the sole dominance of hydrogenotrophic production and the appearance of acetoclastic at full thaw to consider the co-occurrence of methylotrophy throughout. Collectively, these findings indicate that methanogenic and bacterial methylotrophy may be an important and previously underappreciated component of carbon cycling and emissions in these rapidly changing wetland habitats.IMPORTANCEWetlands are the biggest natural source of atmospheric methane (CH4) emissions, yet we have an incomplete understanding of the suite of microbial metabolism that results in CH4 formation. Specifically, methanogenesis from methylated compounds is excluded from all ecosystem models used to predict wetland contributions to the global CH4 budget. Though recent studies have shown methylotrophic methanogenesis to be active across wetlands, the broad climatic importance of the metabolism remains critically understudied. Further, some methylotrophic bacteria are known to produce methanogenic by-products like acetate, increasing the complexity of the microbial methylotrophic metabolic network. Prior studies of Stordalen Mire have suggested that methylotrophic methanogenesis is irrelevant in situ and have not emphasized the bacterial capacity for metabolism, both of which we countered in this study. The importance of our findings lies in the significant advancement toward unraveling the broader impact of methylotrophs in wetland methanogenesis and, consequently, their contribution to the terrestrial global carbon cycle.

Gut microbiome carbon and sulfur metabolisms support Salmonella during pathogen infection

Salmonella enterica serovar Typhimurium is a pervasive enteric pathogen and an ongoing global threat to public health. Ecological studies in the Salmonella impacted gut remain underrepresented in the literature, discounting the microbiome mediated interactions that may inform Salmonella physiology during colonization and infection. To understand the microbial ecology of Salmonella remodeling of the gut microbiome, here we performed multi-omics approaches on fecal microbial communities from untreated and Salmonella -infected mice. Reconstructed genomes recruited metatranscriptomic and metabolomic data providing a strain-resolved view of the expressed metabolisms of the microbiome during Salmonella infection. This data informed possible Salmonella interactions with members of the gut microbiome that were previously uncharacterized. Salmonella- induced inflammation significantly reduced the diversity of transcriptionally active members in the gut microbiome, yet increased gene expression was detected for 7 members, with Luxibacter and Ligilactobacillus being the most active. Metatranscriptomic insights from Salmonella and other persistent taxa in the inflamed microbiome further expounded the necessity for oxidative tolerance mechanisms to endure the host inflammatory responses to infection. In the inflamed gut lactate was a key metabolite, with microbiota production and consumption reported amongst transcriptionally active members. We also showed that organic sulfur sources could be converted by gut microbiota to yield inorganic sulfur pools that become oxidized in the inflamed gut, resulting in thiosulfate and tetrathionate that supports Salmonella respiration. Advancement of pathobiome understanding beyond inferences from prior amplicon-based approaches can hold promise for infection mitigation, with the active community outlined here offering intriguing organismal and metabolic therapeutic targets.

Low-flow in aortic valve stenosis patients with reduced ejection fraction does not depend on left ventricular function

BACKGROUND

Patients with severe aortic stenosis (AS) and reduced left ventricular ejection fraction (LVEF) can be distinguished into high- (HG) and low-gradient (LG) subgroups. However, less is known about their characteristics and underlying (pathophysiological) hemodynamic mechanisms.

METHODS

98 AS patients with reduced LVEF were included. Subgroup characteristics were analyzed by a multimodal approach using clinical and histological data, next-generation sequencing (NGS) and applying echocardiography as well as cardiovascular magnetic resonance (CMR) imaging. Biopsy samples were analyzed with respect to fibrosis and mRNA expression profiles.

RESULTS

40 patients were classified as HG-AS and 58 patients as LG-AS. Severity of AS was comparable between the subgroups. Comparison of both subgroups revealed no differences in LVEF (p = 0.1), LV mass (p = 0.6) or end-diastolic LV diameter (p = 0.12). Neither histological (HG: 23.2% vs. LG: 25.6%, p = 0.73) and circulating biomarker-based assessment (HG: 2.6 ± 2.2% vs. LG: 3.2 ± 3.1%; p = 0.46) of myocardial fibrosis nor global gene expression patterns differed between subgroups. Mitral regurgitation (MR), atrial fibrillation (AF) and impaired right ventricular function (MR: HG: 8% vs. LG: 24%; p < 0.001; AF: HG: 30% vs. LG: 51.7%; p = 0.03; RVSVi: HG 36.7 vs. LG 31.1 ml/m2, p = 0.045; TAPSE: HG 20.2 vs. LG 17.3 mm, p = 0.002) were more frequent in LG-AS patients compared to HG-AS. These pathologies could explain the higher mortality of LG vs. HG-AS patients.

CONCLUSION

In patients with low-flow severe aortic stenosis, low transaortic gradient and cardiac output are not primarily due to LV dysfunction or global changes in gene expression, but may be attributed to other additional cardiac pathologies like mitral regurgitation, atrial fibrillation or right ventricular dysfunction. These factors should also be considered during planning of aortic valve replacement.

Gut microbiota carbon and sulfur metabolisms support Salmonella infections

Salmonella enterica serovar Typhimurium is a pervasive enteric pathogen and ongoing global threat to public health. Ecological studies in the Salmonella impacted gut remain underrepresented in the literature, discounting microbiome mediated interactions that may inform Salmonella physiology during colonization and infection. To understand the microbial ecology of Salmonella remodeling of the gut microbiome, we performed multi-omics on fecal microbial communities from untreated and Salmonella-infected mice. Reconstructed genomes recruited metatranscriptomic and metabolomic data providing a strain-resolved view of the expressed metabolisms of the microbiome during Salmonella infection. These data informed possible Salmonella interactions with members of the gut microbiome that were previously uncharacterized. Salmonella-induced inflammation significantly reduced the diversity of genomes that recruited transcripts in the gut microbiome, yet increased transcript mapping was observed for seven members, among which Luxibacter and Ligilactobacillus transcript read recruitment was most prevalent. Metatranscriptomic insights from Salmonella and other persistent taxa in the inflamed microbiome further expounded the necessity for oxidative tolerance mechanisms to endure the host inflammatory responses to infection. In the inflamed gut lactate was a key metabolite, with microbiota production and consumption reported amongst members with detected transcript recruitment. We also showed that organic sulfur sources could be converted by gut microbiota to yield inorganic sulfur pools that become oxidized in the inflamed gut, resulting in thiosulfate and tetrathionate that support Salmonella respiration. This research advances physiological microbiome insights beyond prior amplicon-based approaches, with the transcriptionally active organismal and metabolic pathways outlined here offering intriguing intervention targets in the Salmonella-infected intestine.

Differential Gene Expression Patterns in Peach Roots under Non-Uniform Soil Conditions in Response to Organic Matter

Organic matter (OM) amendments are often encouraged in sustainable agriculture programs but can create heterogeneous soil environments when applied to perennial crops such as peaches (Prunus persica (L.) Batsch). To better understand the responses of peach roots to non-uniform soil conditions, transcriptomic analysis was performed in a split-root study using uniform soil (the same soil type for all roots) or non-uniform soil (different soil types for each half of the root system) from either (1) autoclaved sand (S), (2) autoclaved sand with autoclaved compost (A), or (3) autoclaved sand with compost which included inherent biological soil life (B). Each uniform soil type (S, A, and B) was grouped and compared by uniform and non-uniform soil comparisons for a total of nine treatments. Comparisons revealed peach roots had differentially expressed genes (DEGs) and gene ontology terms between soil groups, with the S and B groups having a range of 106-411 DEGs and the A group having a range of 19-94 DEGs. Additionally, six modules were identified and correlated (p > 0.69) for six of the nine treatment combinations. This study broadly highlights the complexity of how OM and biological life in the rhizosphere interact with immediate and distant roots and sheds light on how non-homogenous soil conditions can influence peach root gene expression.

Subconfluent ARPE-19 Cells Display Mesenchymal Cell-State Characteristics and Behave like Fibroblasts, Rather Than Epithelial Cells, in Experimental HCMV Infection Studies

Human cytomegalovirus (HCMV) has a broad cellular tropism and epithelial cells are important physiological targets during infection. The retinal pigment epithelial cell line ARPE-19 has been used to model HCMV infection in epithelial cells for decades and remains a commonly used cell type for studying viral entry, replication, and the cellular response to infection. We previously found that ARPE-19 cells, despite being derived from an epithelial cell explant, express extremely low levels of canonical epithelial proteins, such as E-cadherin and EpCAM. Here, we perform comparative studies of ARPE-19 and additional epithelial cell lines with strong epithelial characteristics. We find that ARPE-19 cells cultured under subconfluent conditions resemble mesenchymal fibroblasts, rather than epithelial cells; this is consistent with previous studies showing that ARPE-19 cultures require extended periods of high confluency culture to maintain epithelial characteristics. By reanalyzing public gene expression data and using machine learning, we find evidence that ARPE-19 cultures maintained across many labs exhibit mesenchymal characteristics and that the majority of studies employing ARPE-19 use them in a mesenchymal state. Lastly, by performing experimental HCMV infections across mesenchymal and epithelial cell lines, we find that ARPE-19 cells behave like mesenchymal fibroblasts, producing logarithmic yields of cell-free infectious progeny, while cell lines with strong epithelial character exhibit an atypical infectious cycle and naturally restrict the production of cell-free progeny. Our work highlights important characteristics of the ARPE-19 cell line and suggests that subconfluent ARPE-19 cells may not be optimal for modeling epithelial infection with HCMV or other human viruses. It also suggests that HCMV biosynthesis and/or spread may occur quite differently in epithelial cells compared to mesenchymal cells. These differences could contribute to viral persistence or pathogenesis in epithelial tissues.

Gene family expansion analysis and identification of the histone family in Spodoptera frugiperda

Spodoptera frugiperda, a major invasive pest, causes severe damage to various economically important crops. Previous comparative genomics studies have revealed a close association between the invasiveness of S. frugiperda and its genome. In recent years, a vast amount of genome from lepidopteran species has become available, offering an opportunity for a more detailed and comprehensive understanding of the biological characteristics of S. frugiperda. In this study, we conducted a comprehensive comparative genomics analysis of S. frugiperda using genome from 46 lepidopteran species. We found the highest number of gene family expansion events in S. frugiperda, indicating that gene family expansion is a crucial mechanism in its adaptive evolution. The expanded gene families are enriched in various biological processes, including nutrient metabolism, development, stress response, reproduction, and immune processes, suggesting that the expansion of these gene families likely contributes to the strong environmental adaptability of S. frugiperda. Furthermore, we identified the expansion of histone gene families in S. frugiperda which resulted from chromosome segmental duplications after the divergence from closely related species. Expression analysis of histone genes indicated that certain members might exert an influence on the growth and reproduction processes of S. frugiperda. Overall, our study deepens our understanding of the biological characteristics of S. frugiperda, providing a theoretical basis for the comprehensive management and sustained control of S. frugiperda and other lepidopteran pests in the future.

Integrative whole-genome and transcriptome analysis of HER2-amplified metastatic breast cancer

BACKGROUND

In breast cancer, the advent of anti-HER2 therapies has made HER2+ tumors a highly relevant subgroup. However, the exact characteristics which prohibit clinical response to anti-HER2 therapies and drive disease progression are not yet fully known. Integrative whole-genome and transcriptomic sequencing data from both primary and metastatic HER2-positive breast cancer will enhance our understanding of underlying biological processes.

METHODS

Here, we used WGS and RNA sequencing data of 700 metastatic breast tumors, of which 68 being HER2+, to search for specific genomic features of HER2+ disease and therapy resistance. Furthermore, we integrated results with transcriptomic data to associate tumors exhibiting a HER2+-specific gene expression profile with ERBB2 mutation status, prior therapy and relevant gene expression signatures.

RESULTS

Overall genomic profiles of primary and metastatic HER2+ breast cancers were similar, and no specific acquired genomics traits connected to prior anti-HER2 treatment were observed. However, specific genomic features were predictive of progression-free survival on post-biopsy anti-HER2 treatment. Furthermore, a HER2-driven expression profile grouped HER2-amplified tumors with ERBB2-mutated cases and cases without HER2 alterations. The latter were reported as ER positive in primary disease, but the metastatic biopsy showed low ESR1 expression and upregulation of the MAPK pathway, suggesting transformation to ER independence.

CONCLUSIONS

In summary, although the quantity of variants increased throughout HER2-positive breast cancer progression, the genomic composition remained largely consistent, thus yielding no new major processes beside those already operational in primary disease. Our results suggest that integrated genomic and transcriptomic analyses may be key in establishing therapeutic options.

Trehalose metabolism coordinates transcriptional regulatory control and metabolic requirements to trigger the onset of cassava storage root initiation

Cassava storage roots (SR) are an important source of food energy and raw material for a wide range of applications. Understanding SR initiation and the associated regulation is critical to boosting tuber yield in cassava. Decades of transcriptome studies have identified key regulators relevant to SR formation, transcriptional regulation and sugar metabolism. However, there remain uncertainties over the roles of the regulators in modulating the onset of SR development owing to the limitation of the widely applied differential gene expression analysis. Here, we aimed to investigate the regulation underlying the transition from fibrous (FR) to SR based on Dynamic Network Biomarker (DNB) analysis. Gene expression analysis during cassava root initiation showed the transition period to SR happened in FR during 8 weeks after planting (FR8). Ninety-nine DNB genes associated with SR initiation and development were identified. Interestingly, the role of trehalose metabolism, especially trehalase1 (TRE1), in modulating metabolites abundance and coordinating regulatory signaling and carbon substrate availability via the connection of transcriptional regulation and sugar metabolism was highlighted. The results agree with the associated DNB characters of TRE1 reported in other transcriptome studies of cassava SR initiation and Attre1 loss of function in literature. The findings help fill the knowledge gap regarding the regulation underlying cassava SR initiation.

Targeted curation of the gut microbial gene content modulating human cardiovascular disease

IMPORTANCE

One of the most-cited examples of the gut microbiome modulating human disease is the microbial metabolism of quaternary amines from protein-rich foods. By-products of this microbial processing promote atherosclerotic heart disease, a leading cause of human mortality globally. Our research addresses current knowledge gaps in our understanding of this microbial metabolism by holistically inventorying the microorganisms and expressed genes catalyzing critical atherosclerosis-promoting and -ameliorating reactions in the human gut. This led to the creation of an open-access resource, the Methylated Amine Gene Inventory of Catabolism database, the first systematic inventory of gut methylated amine metabolism. More importantly, using this resource we deliver here, we show for the first time that these gut microbial genes can predict human disease, paving the way for microbiota-inspired diagnostics and interventions.

Master regulator activity QTL protocol to implicate regulatory pathways potentially mediating GWAS signals using eQTL data

Here, we present a protocol to identify transcriptional regulators potentially mediating downstream biological effects of germline variants associated with complex traits of interest, which enables functional hypothesis generation independent of colocalizing expression quantitative trait loci (eQTLs). We describe steps for tissue-/cell-type-specific co-expression network modeling, expression regulator activity inference, and identification of representative phenotypic master regulators. Finally, we detail activity QTL and eQTL analyses. This protocol requires genotype, expression, and relevant covariables and phenotype data from existing eQTL datasets. For complete details on the use and execution of this protocol, please refer to Hoskins et al.1.

Genomic Alterations Associated with Estrogen Receptor Pathway Activity in Metastatic Breast Cancer Have a Differential Impact on Downstream ER Signaling

Mutations in the estrogen receptor gene (ESR1), its transcriptional regulators, and the mitogen-activated protein kinase (MAPK) pathway are enriched in patients with endocrine-resistant metastatic breast cancer (MBC). Here, we integrated whole genome sequencing with RNA sequencing data from the same samples of 101 ER-positive/HER2-negative MBC patients who underwent a tumor biopsy prior to the start of a new line of treatment for MBC (CPCT-02 study, NCT01855477) to analyze the downstream effects of DNA alterations previously linked to endocrine resistance, thereby gaining a better understanding of the associated mechanisms. Hierarchical clustering was performed using expression of ESR1 target genes. Genomic alterations at the DNA level, gene expression levels, and last administered therapy were compared between the identified clusters. Hierarchical clustering revealed two distinct clusters, one of which was characterized by increased expression of ESR1 and its target genes. Samples in this cluster were significantly enriched for mutations in ESR1 and amplifications in FGFR1 and TSPYL. Patients in the other cluster showed relatively lower expression levels of ESR1 and its target genes, comparable to ER-negative samples, and more often received endocrine therapy as their last treatment before biopsy. Genes in the MAPK-pathway, including NF1, and ESR1 transcriptional regulators were evenly distributed. In conclusion, RNA sequencing identified a subgroup of patients with clear expression of ESR1 and its downstream targets, probably still benefiting from ER-targeting agents. The lower ER expression in the other subgroup might be partially explained by ER activity still being blocked by recently administered endocrine treatment, indicating that biopsy timing relative to endocrine treatment needs to be considered when interpreting transcriptomic data.