Replisome Proximal Protein Associations and Dynamic Proteomic Changes at Stalled Replication Forks.

DNA replication is a fundamental cellular process that ensures the transfer of genetic information during cell division. Genome duplication takes place in S phase and requires a dynamic and highly coordinated recruitment of multiple proteins at replication forks. Various genotoxic stressors lead to fork instability and collapse, hence the need for DNA repair pathways. By identifying the multitude of protein interactions implicated in those events, we can better grasp the complex and dynamic molecular mechanisms that facilitate DNA replication and repair. Proximity-dependent biotin identification was used to identify associations with 17 proteins within four core replication components, namely the CDC45/MCM2-7/GINS helicase that unwinds DNA, the DNA polymerases, replication protein A subunits, and histone chaperones needed to disassemble and reassemble chromatin. We further investigated the impact of genotoxic stress on these interactions. This analysis revealed a vast proximity association network with 108 nuclear proteins further modulated in the presence of hydroxyurea; 45 being enriched and 63 depleted. Interestingly, hydroxyurea treatment also caused a redistribution of associations with 11 interactors, meaning that the replisome is dynamically reorganized when stressed. The analysis identified several poorly characterized proteins, thereby uncovering new putative players in the cellular response to DNA replication arrest. It also provides a new comprehensive proteomic framework to understand how cells respond to obstacles during DNA replication.

The regulatory roles of small nucleolar RNAs within their host locus.

Small nucleolar RNAs (snoRNAs) are a class of conserved noncoding RNAs forming complexes with proteins to catalyse site-specific modifications on ribosomal RNA. Besides this canonical role, several snoRNAs are now known to regulate diverse levels of gene expression. While these functions are carried out in trans by mature snoRNAs, evidence has also been emerging of regulatory roles of snoRNAs in cis, either within their genomic locus or as longer transcription intermediates during their maturation. Herein, we review recent findings that snoRNAs can interact in cis with their intron to regulate the expression of their host gene. We also explore the ever-growing diversity of longer host-derived snoRNA extensions and their functional impact across the transcriptome. Finally, we discuss the role of snoRNA duplications into forging these new layers of snoRNA-mediated regulation, as well as their involvement in the genomic imprinting of their host locus.

Apelin stimulation of the vascular skeletal muscle stem cell niche enhances endogenous repair in dystrophic mice.

Impaired skeletal muscle stem cell (MuSC) function has long been suspected to contribute to the pathogenesis of muscular dystrophy (MD). Here, we showed that defects in the endothelial cell (EC) compartment of the vascular stem cell niche in mouse models of Duchenne MD, laminin α2-related MD, and collagen VI-related myopathy were associated with inefficient mobilization of MuSCs after tissue damage. Using chemoinformatic analysis, we identified the 13-amino acid form of the peptide hormone apelin (AP-13) as a candidate for systemic stimulation of skeletal muscle ECs. Systemic administration of AP-13 using osmotic pumps generated a pro-proliferative EC-rich niche that supported MuSC function through angiocrine factors and markedly improved tissue regeneration and muscle strength in all three dystrophic mouse models. Moreover, EC-specific knockout of the apelin receptor led to regenerative defects that phenocopied key pathological features of MD, including vascular defects, fibrosis, muscle fiber necrosis, impaired MuSC function, and reduced force generation. Together, these studies provide in vivo proof of concept that enhancing endogenous skeletal muscle repair by targeting the vascular niche is a viable therapeutic avenue for MD and characterized AP-13 as a candidate for further study for the systemic treatment of MuSC dysfunction.

OpenProt 2.0 builds a path to the functional characterization of alternative proteins.

The OpenProt proteogenomic resource (https://www.openprot.org/) provides users with a complete and freely accessible set of non-canonical or alternative open reading frames (AltORFs) within the transcriptome of various species, as well as functional annotations of the corresponding protein sequences not found in standard databases. Enhancements in this update are largely the result of user feedback and include the prediction of structure, subcellular localization, and intrinsic disorder, using cutting-edge algorithms based on machine learning techniques. The mass spectrometry pipeline now integrates a machine learning-based peptide rescoring method to improve peptide identification. We continue to help users explore this cryptic proteome by providing OpenCustomDB, a tool that enables users to build their own customized protein databases, and OpenVar, a genomic annotator including genetic variants within AltORFs and protein sequences. A new interface improves the visualization of all functional annotations, including a spectral viewer and the prediction of multicoding genes. All data on OpenProt are freely available and downloadable. Overall, OpenProt continues to establish itself as an important resource for the exploration and study of new proteins.

Osteoclast microRNA Profiling in Rheumatoid Arthritis to Capture the Erosive Factor.

In rheumatoid arthritis (RA), only a subset of patients develop irreversible bone destruction. Our aim was to identify a microRNA (miR)-based osteoclast-related signature predictive of erosiveness in RA. Seventy-six adults with erosive (E) or nonerosive (NE) seropositive RA and 43 sex- and age-matched healthy controls were recruited. Twenty-five miRs from peripheral blood mononuclear cell (PBMC)-derived osteoclasts selected from RNA-Seq (discovery cohort) were assessed by qPCR (replication cohort), as were 33 target genes (direct targets or associated with regulated pathways). The top five miRs found differentially expressed in RA osteoclasts were either decreased (hsa-miR-34a-3p, 365b-3p, 374a-3p, and 511-3p [E versus NE]) or increased (hsa-miR-193b-3p [E versus controls]). In vitro, inhibition of miR-34a-3p had an impact on osteoclast bone resorption. An integrative network analysis of miRs and their targets highlighted correlations between mRNA and miR expression, both negative (CD38, CD80, SIRT1) and positive (MITF), and differential gene expression between NE versus E (GXYLT1, MITF) or versus controls (CD38, KLF4). Machine-learning models were used to evaluate the value of miRs and target genes, in combination with clinical data, to predict erosion. One model, including a set of miRs (predominantly 365b-3p) combined with rheumatoid factor titer, provided 70% accuracy (area under the curve [AUC] 0.66). Adding genes directly targeted or belonging to related pathways improved the predictive power of the model for the erosive phenotype (78% accuracy, AUC 0.85). This proof-of-concept study indicates that identification of RA subjects at risk of erosions may be improved by studying miR expression in PBMC-derived osteoclasts, suggesting novel approaches toward personalized treatment. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Isocitrate dehydrogenase wt and IDHmut adult-type diffuse gliomas display distinct alterations in ribosome biogenesis and 2'O-methylation of ribosomal RNA.

BACKGROUND: High-grade adult-type diffuse gliomas (HGGs) constitute a heterogeneous group of aggressive tumors that are mostly incurable. Recent advances highlighting the contribution of ribosomes to cancer development have offered new clinical perspectives. Here, we uncovered that isocitrate dehydrogenase (IDH)wt and IDHmut HGGs display distinct alterations of ribosome biology, in terms of rRNA epitranscriptomics and ribosome biogenesis, which could constitute novel hallmarks that can be exploited for the management of these pathologies. METHODS: We analyzed (1) the ribosomal RNA 2'O-ribose methylation (rRNA 2'Ome) using RiboMethSeq and in-house developed bioinformatics tools (https://github.com/RibosomeCRCL/ribomethseq-nfandrRMSAnalyzer) on 3 independent cohorts compiling 71 HGGs (IDHwt n = 30, IDHmut n = 41) and 9 non-neoplastic samples, (2) the expression of ribosome biogenesis factors using medium throughput RT-qPCR as a readout of ribosome biogenesis, and (3) the sensitivity of 5 HGG cell lines to RNA Pol I inhibitors (CX5461, BMH-21). RESULTS: Unsupervised analysis demonstrated that HGGs could be distinguished based on their rRNA 2'Ome epitranscriptomic profile, with IDHwt glioblastomas displaying the most significant alterations of rRNA 2'Ome at specific sites. In contrast, IDHmut HGGs are largely characterized by an overexpression of ribosome biogenesis factors compared to non-neoplastic tissues or IDHwt glioblastomas. Finally, IDHmut HGG-derived spheroids display higher cytotoxicity to CX5461 than IDHwt glioblastoma, while all HGG spheroids display a similar cytotoxicity to BMH-21. CONCLUSIONS: In HGGs, IDH mutational status is associated with specific alterations of the ribosome biology and with distinct sensitivities to RNA Pol I inhibitors.

Intronic small nucleolar RNAs regulate host gene splicing through base pairing with their adjacent intronic sequences.

BACKGROUND: Small nucleolar RNAs (snoRNAs) are abundant noncoding RNAs best known for their involvement in ribosomal RNA maturation. In mammals, most expressed snoRNAs are embedded in introns of longer genes and produced through transcription and splicing of their host. Intronic snoRNAs were long viewed as inert passengers with little effect on host expression. However, a recent study reported a snoRNA influencing the splicing and ultimate output of its host gene. Overall, the general contribution of intronic snoRNAs to host expression remains unclear. RESULTS: Computational analysis of large-scale human RNA-RNA interaction datasets indicates that 30% of detected snoRNAs interact with their host transcripts. Many snoRNA-host duplexes are located near alternatively spliced exons and display high sequence conservation suggesting a possible role in splicing regulation. The study of the model SNORD2-EIF4A2 duplex indicates that the snoRNA interaction with the host intronic sequence conceals the branch point leading to decreased inclusion of the adjacent alternative exon. Extended SNORD2 sequence containing the interacting intronic region accumulates in sequencing datasets in a cell-type-specific manner. Antisense oligonucleotides and mutations that disrupt the formation of the snoRNA-intron structure promote the splicing of the alternative exon, shifting the EIF4A2 transcript ratio away from nonsense-mediated decay. CONCLUSIONS: Many snoRNAs form RNA duplexes near alternative exons of their host transcripts, placing them in optimal positions to control host output as shown for the SNORD2-EIF4A2 model system. Overall, our study supports a more widespread role for intronic snoRNAs in the regulation of their host transcript maturation.

Kunjin Virus, Zika Virus, and Yellow Fever Virus Infections Have Distinct Effects on the Coding Transcriptome and Proteome of Brain-Derived U87 Cells.

As obligate intracellular parasites, viruses rely heavily on host cells for replication, and therefore dysregulate several cellular processes for their benefit. In return, host cells activate multiple signaling pathways to limit viral replication and eradicate viruses. The present study explores the complex interplay between viruses and host cells through next generation RNA sequencing as well as mass spectrometry (SILAC). Both the coding transcriptome and the proteome of human brain-derived U87 cells infected with Kunjin virus, Zika virus, or Yellow Fever virus were compared to the transcriptome and the proteome of mock-infected cells. Changes in the abundance of several hundred mRNAs and proteins were found in each infection. Moreover, the alternative splicing of hundreds of mRNAs was found to be modulated upon viral infection. Interestingly, a significant disconnect between the changes in the transcriptome and those in the proteome of infected cells was observed. These findings provide a global view of the coding transcriptome and the proteome of Flavivirus-infected cells, leading to a better comprehension of Flavivirus-host interactions.

Motif conservation, stability, and host gene expression are the main drivers of snoRNA expression across vertebrates.

Small nucleolar RNAs (snoRNAs) are structured noncoding RNAs present in multiple copies within eukaryotic genomes. snoRNAs guide chemical modifications on their target RNA and regulate processes like ribosome assembly and splicing. Most human snoRNAs are embedded within host gene introns, the remainder being independently expressed from intergenic regions. We recently characterized the abundance of snoRNAs and their host gene across several healthy human tissues and found that the level of most snoRNAs does not correlate with that of their host gene, with the observation that snoRNAs embedded within the same host gene often differ drastically in abundance. To better understand the determinants of snoRNA expression, we trained machine learning models to predict whether snoRNAs are expressed or not in human tissues based on more than 30 collected features related to snoRNAs and their genomic context. By interpreting the models' predictions, we find that snoRNAs rely on conserved motifs, a stable global structure and terminal stem, and a transcribed locus to be expressed. We observe that these features explain well the varying abundance of snoRNAs embedded within the same host gene. By predicting the expression status of snoRNAs across several vertebrates, we notice that only one-third of all annotated snoRNAs are expressed per genome, as in humans. Our results suggest that ancestral snoRNAs disseminated within vertebrate genomes, sometimes leading to the development of new functions and a probable gain in fitness and thereby conserving features favorable to the expression of these few snoRNAs, the large remainder often degenerating into pseudogenes.

snoDB 2.0: an enhanced interactive database, specializing in human snoRNAs.

snoDB is an interactive database of human small nucleolar RNAs (snoRNAs) that includes up-to-date information on snoRNA features, genomic location, conservation, host gene, snoRNA-RNA targets and snoRNA abundance and provides links to other resources. In the second edition of this database (snoDB 2.0), we added an entirely new section on ribosomal RNA (rRNA) chemical modifications guided by snoRNAs with easy navigation between the different rRNA versions used in the literature and experimentally measured levels of modification. We also included new layers of information, including snoRNA motifs, secondary structure prediction, snoRNA-protein interactions, copy annotations and low structure bias expression data in a wide panel of tissues and cell lines to bolster functional probing of snoRNA biology. Version 2.0 features updated identifiers, more links to external resources and duplicate entry resolution. As a result, snoDB 2.0, which is freely available at https://bioinfo-scottgroup.med.usherbrooke.ca/snoDB/, represents a one-stop shop for snoRNA features, rRNA modification targets, functional impact and potential regulators.

First Trimester Plasma MicroRNA Levels Predict Risk of Developing Gestational Diabetes Mellitus.

Aims: Our objective is to identify first-trimester plasmatic miRNAs associated with and predictive of GDM. Methods: We quantified miRNA using next-generation sequencing in discovery (Gen3G: n = 443/GDM = 56) and replication (3D: n = 139/GDM = 76) cohorts. We have diagnosed GDM using a 75-g oral glucose tolerance test and the IADPSG criteria. We applied stepwise logistic regression analysis among replicated miRNAs to build prediction models. Results: We identified 17 miRNAs associated with GDM development in both cohorts. The prediction performance of hsa-miR-517a-3p|hsa-miR-517b-3p, hsa-miR-218-5p, and hsa-let7a-3p was slightly better than GDM classic risk factors (age, BMI, familial history of type 2 diabetes, history of GDM or macrosomia, and HbA1c) (AUC 0.78 vs. 0.75). MiRNAs and GDM classic risk factors together further improved the prediction values [AUC 0.84 (95% CI 0.73-0.94)]. These results were replicated in 3D, although weaker predictive values were obtained. We suggest very low and higher risk GDM thresholds, which could be used to identify women who could do without a diagnostic test for GDM and women most likely to benefit from an early GDM prevention program. Conclusions: In summary, three miRNAs combined with classic GDM risk factors provide excellent prediction values, potentially strong enough to improve early detection and prevention of GDM.

Altered tRNA processing is linked to a distinct and unusual La protein in Tetrahymena thermophila.

Nascent pre-tRNAs are transcribed by RNA polymerase III and immediately bound by La proteins on the UUU-3'OH sequence, using a tandem arrangement of the La motif and an adjacent RNA recognition motif-1 (RRM1), resulting in protection from 3'-exonucleases and promotion of pre-tRNA folding. The Tetrahymena thermophila protein Mlp1 has been previously classified as a genuine La protein, despite the predicted absence of the RRM1. We find that Mlp1 functions as a La protein through binding of pre-tRNAs, and affects pre-tRNA processing in Tetrahymena thermophila and when expressed in fission yeast. However, unlike in other examined eukaryotes, depletion of Mlp1 results in 3'-trailer stabilization. The 3'-trailers in Tetrahymena thermophila are uniquely short relative to other examined eukaryotes, and 5'-leaders have evolved to disfavour pre-tRNA leader/trailer pairing. Our data indicate that this variant Mlp1 architecture is linked to an altered, novel mechanism of tRNA processing in Tetrahymena thermophila.

Newfound Coding Potential of Transcripts Unveils Missing Members of Human Protein Communities.

Recent proteogenomic approaches have led to the discovery that regions of the transcriptome previously annotated as non-coding regions [i.e., untranslated regions (UTRs), open reading frames overlapping annotated coding sequences in a different reading frame, and non-coding RNAs] frequently encode proteins, termed alternative proteins (altProts). This suggests that previously identified protein-protein interaction (PPI) networks are partially incomplete because altProts are not present in conventional protein databases. Here, we used the proteogenomic resource OpenProt and a combined spectrum- and peptide-centric analysis for the re-analysis of a high-throughput human network proteomics dataset thereby revealing the presence of 261 altProts in the network. We found 19 genes encoding both an annotated (reference) and an alternative protein interacting with each other. Of the 117 altProts encoded by pseudogenes, 38 are direct interactors of reference proteins encoded by their respective parental gene. Finally, we experimentally validate several interactions involving altProts. These data improve the blueprints of the human PPI network and suggest functional roles for hundreds of altProts.

Duplicated ribosomal protein paralogs promote alternative translation and drug resistance.

Ribosomes are often seen as monolithic machines produced from uniformly regulated genes. However, in yeast most ribosomal proteins come from duplicated genes. Here, we demonstrate that gene duplication may serve as a stress-adaptation mechanism modulating the global proteome through the differential expression of ribosomal protein paralogs. Our data indicate that the yeast paralog pair of the ribosomal protein L7/uL30 produces two differentially acetylated proteins. Under normal conditions most ribosomes incorporate the hypo-acetylated major form favoring the translation of genes with short open reading frames. Exposure to drugs, on the other hand, increases the production of ribosomes carrying the hyper-acetylated minor paralog that increases translation of long open reading frames. Many of these paralog-dependent genes encode cell wall proteins that could promote tolerance to drugs as their translation increases after exposure to drugs. Together our data suggest a mechanism of translation control that functions through a differential use of near-identical ribosomal protein isoforms.

Maternal Body Mass Index Is Associated with Profile Variation in Circulating MicroRNAs at First Trimester of Pregnancy.

Many women enter pregnancy with overweight and obesity, which are associated with complications for both the expectant mother and her child. MicroRNAs (miRNAs) are short non-coding RNAs that regulate many biological processes, including energy metabolism. Our study aimed to identify first trimester plasmatic miRNAs associated with maternal body mass index (BMI) in early pregnancy. We sequenced a total of 658 plasma samples collected between the 4th and 16th week of pregnancy from two independent prospective birth cohorts (Gen3G and 3D). In each cohort, we assessed associations between early pregnancy maternal BMI and plasmatic miRNAs using DESeq2 R package, adjusting for sequencing run and lane, gestational age, maternal age at the first trimester of pregnancy and parity. A total of 38 miRNAs were associated (FDR q < 0.05) with BMI in the Gen3G cohort and were replicated (direction and magnitude of the fold change) in the 3D cohort, including 22 with a nominal p-value < 0.05. Some of these miRNAs were enriched in fatty acid metabolism-related pathways. We identified first trimester plasmatic miRNAs associated with maternal BMI. These miRNAs potentially regulate fatty acid metabolism-related pathways, supporting the hypothesis of their potential contribution to energy metabolism regulation in early pregnancy.

The snoGloBe interaction predictor reveals a broad spectrum of C/D snoRNA RNA targets.

Box C/D small nucleolar RNAs (snoRNAs) are a conserved class of RNA known for their role in guiding ribosomal RNA 2'-O-ribose methylation. Recently, C/D snoRNAs were also implicated in regulating the expression of non-ribosomal genes through different modes of binding. Large scale RNA-RNA interaction datasets detect many snoRNAs binding messenger RNA, but are limited by specific experimental conditions. To enable a more comprehensive study of C/D snoRNA interactions, we created snoGloBe, a human C/D snoRNA interaction predictor based on a gradient boosting classifier. SnoGloBe considers the target type, position and sequence of the interactions, enabling it to outperform existing predictors. Interestingly, for specific snoRNAs, snoGloBe identifies strong enrichment of interactions near gene expression regulatory elements including splice sites. Abundance and splicing of predicted targets were altered upon the knockdown of their associated snoRNA. Strikingly, the predicted snoRNA interactions often overlap with the binding sites of functionally related RNA binding proteins, reinforcing their role in gene expression regulation. SnoGloBe is also an excellent tool for discovering viral RNA targets, as shown by its capacity to identify snoRNAs targeting the heavily methylated SARS-CoV-2 RNA. Overall, snoGloBe is capable of identifying experimentally validated binding sites and predicting novel sites with shared regulatory function.

SAPFIR: A webserver for the identification of alternative protein features.

BACKGROUND: Alternative splicing can increase the diversity of gene functions by generating multiple isoforms with different sequences and functions. However, the extent to which splicing events have functional consequences remains unclear and predicting the impact of splicing events on protein activity is limited to gene-specific analysis. RESULTS: To accelerate the identification of functionally relevant alternative splicing events we created SAPFIR, a predictor of protein features associated with alternative splicing events. This webserver tool uses InterProScan to predict protein features such as functional domains, motifs and sites in the human and mouse genomes and link them to alternative splicing events. Alternative protein features are displayed as functions of the transcripts and splice sites. SAPFIR could be used to analyze proteins generated from a single gene or a group of genes and can directly identify alternative protein features in large sequence data sets. The accuracy and utility of SAPFIR was validated by its ability to rediscover previously validated alternative protein domains. In addition, our de novo analysis of public datasets using SAPFIR indicated that only a small portion of alternative protein domains was conserved between human and mouse, and that in human, genes involved in nervous system process, regulation of DNA-templated transcription and aging are more likely to produce isoforms missing functional domains due to alternative splicing. CONCLUSION: Overall SAPFIR represents a new tool for the rapid identification of functional alternative splicing events and enables the identification of cellular functions affected by a defined splicing program. SAPFIR is freely available at https://bioinfo-scottgroup.med.usherbrooke.ca/sapfir/ , a website implemented in Python, with all major browsers supported. The source code is available at https://github.com/DelongZHOU/SAPFIR .

Deciphering of Adult Glioma Vulnerabilities through Expression Pattern Analysis of GABA, Glutamate and Calcium Neurotransmitter Genes.

Adult infiltrating gliomas are highly aggressive tumors of the central nervous system with a dismal prognosis despite intensive multimodal therapy (chemotherapy and/or radiotherapy). In this study, we studied the expression, methylation and interacting miRNA profiles of GABA-, glutamate- and calcium-related genes in 661 adult infiltrating gliomas available through the TCGA database. Neurotransmitter-based unsupervised clustering identified three established glioma molecular subgroups that parallel major World Health Organization glioma subclasses (IDH-wildtype astrocytomas, IDH-mutant astrocytomas, IDH-mutant oligodendroglioma). In addition, this analysis also defined a novel, neurotransmitter-related glioma subgroup (NT-1), mostly comprised of IDH-mutated gliomas and characterized by the overexpression of neurotransmitter-related genes. Lower expression of neurotransmission-related genes was correlated with increased aggressivity in hypomethylated IDH-wildtype tumors. There were also significant differences in the composition of the tumor inflammatory microenvironment between neurotransmission-based tumor categories, with lower estimated pools of M2-phenotype macrophages in NT-1 gliomas. This multi-omics analysis of the neurotransmission expression landscape of TCGA gliomas-which highlights the existence of neurotransmission-based glioma categories with different expression, epigenetic and inflammatory profiles-supports the existence of operational neurotransmitter signaling pathways in adult gliomas. These findings could shed new light on potential vulnerabilities to exploit in future glioma-targeting drug therapies.

Downregulation of KRAB zinc finger proteins in 5-fluorouracil resistant colorectal cancer cells.

Radio-chemotherapy with 5-flu orouracil (5-FU) is the standard of care treatment for patients with colorectal cancer, but it is only effective for a third of them. Despite our understanding of the mechanism of action of 5-FU, drug resistance remains a significant limitation to the clinical use of 5-FU, as both intrinsic and acquired chemoresistance represents the major obstacles for the success of 5-FU-based chemotherapy. In order to identify the mechanism of acquired resistance, 5-FU chemoresistance was induced in CRC cell lines by passaging cells with increasing concentrations of 5-FU. To study global molecular changes, quantitative proteomics and transcriptomics analyses were performed on these cell lines, comparing the resistant cells as well as the effect of chemo and radiotherapy. Interestingly, a very high proportion of downregulated genes were annotated as transcription factors coding for Krüppel-associated box (KRAB) domain-containing zinc-finger proteins (KZFPs), the largest family of transcriptional repressors. Among nearly 350 KRAB-ZFPs, almost a quarter were downregulated after the induction of a 5-FU-resistance including a common one between the three CRC cell lines, ZNF649, whose role is still unknown. To confirm the observations of the proteomic and transcriptomic approaches, the abundance of 20 different KZFPs and control mRNAs was validated by RT-qPCR. In fact, several KZFPs were no longer detectable using qPCR in cell lines resistant to 5-FU, and the KZFPs that were downregulated only in one or two cell lines showed similar pattern of expression as measured by the omics approaches. This proteomic, transcriptomic and genomic analysis of intrinsic and acquired resistance highlights a possible new mechanism involved in the cellular adaptation to 5-FU and therefore identifies potential new therapeutic targets to overcome this resistance.

First trimester plasma microRNAs levels predict Matsuda Index-estimated insulin sensitivity between 24th and 29th week of pregnancy.

INTRODUCTION: Gestational diabetes mellitus (GDM) is a consequence of an imbalance between insulin sensitivity (IS) and secretion during pregnancy. MicroRNAs (miRNAs) are small and secreted RNA molecules stable in blood and known to regulate physiological processes including glucose homeostasis. The aim of this study was to identify plasmatic miRNAs detectable in early pregnancy predicting IS at 24th-29th week of pregnancy. RESEARCH DESIGN AND METHODS: We quantified circulating miRNAs in 421 women in plasma collected at 9.6±2.2 weeks of pregnancy using next-generation sequencing. RESULTS: we detected 2170 miRNAs: 39 (35 positively and 4 negatively) were associated with IS as estimated by the Matsuda Index at 26.4±1.0 weeks of pregnancy. Lasso regression identified 18 miRNAs independently predicting Matsuda Index-estimated IS. Together with gestational age, maternal age and body mass index at first trimester, they explain 36% of IS variance in late second trimester of pregnancy. These miRNAs regulate fatty acid biosynthesis and metabolism among other pathways. CONCLUSIONS: In summary, we have identified first trimester plasmatic miRNAs predictive of Matsuda Index-estimated IS in late second trimester of pregnancy. These miRNAs could also contribute to initiate and support IS adaptation to pregnancy potentially through lipid metabolism regulation.