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The gastrointestinal tract (GIT) microbiota has been identified as an important reservoir of antibiotic resistance genes (ARGs) that can be horizontally transferred to pathogenic species. Maternal GIT microbes can be transmitted to the offspring, and recent work indicates that such transfer starts before birth. We have used culture-independent genetic screenings to explore whether ARGs are already present in the meconium accumulated in the GIT during fetal life and in feces of 1-week-old infants. We have analyzed resistance to β-lactam antibiotics (BLr) and tetracycline (Tcr), screening for a variety of genes conferring each. To evaluate whether ARGs could have been inherited by maternal transmission, we have screened perinatal fecal samples of the 1-week-old babies’ mothers, as well as a mother–infant series including meconium, fecal samples collected through the infant’s 1st year, maternal fecal samples and colostrum. Our results reveal a high prevalence of BLr and Tcr in both meconium and early fecal samples, implying that the GIT resistance reservoir starts to accumulate even before birth. We show that ARGs present in the mother may reach the meconium and colostrum and establish in the infant GIT, but also that some ARGs were likely acquired from other sources. Alarmingly, we identified in both meconium and 1-week-olds’ samples a particularly elevated prevalence of mecA (>45%), six-fold higher than that detected in the mothers. The mecA gene confers BLr to methicillin-resistant Staphylococcus aureus, and although its detection does not imply the presence of this pathogen, it does implicate the young infant’s GIT as a noteworthy reservoir of this gene. [ABSTRACT FROM PUBLISHER]

Alternative splicing is crucial for cancer progression and can be targeted pharmacologically, yet identifying driver exons genome-wide remains challenging. We propose identifying such exons by associating statistically gene-level cancer dependencies from knockdown viability screens with splicing profiles and gene expression. Our models predict the effects of splicing perturbations on cell proliferation from transcriptomic data, enabling in silico RNA screening and prioritizing targets for splicing-based therapies. We identified 1,073 exons impacting cell proliferation, many from genes not previously linked to cancer. Experimental validation confirms their influence on proliferation, especially in highly proliferative cancer cell lines. Integrating pharmacological screens with splicing dependencies highlights the potential driver exons affecting drug sensitivity. Our models also allow predicting treatment outcomes from tumor transcriptomes, suggesting applications in precision oncology. This study presents an approach to identifying cancer driver exon and their therapeutic potential, emphasizing alternative splicing as a cancer target., (© 2024. The Author(s).)

A non-pathogenic Mycoplasma pneumoniae-based chassis is leading the development of live biotherapeutic products (LBPs) for respiratory diseases. However, reports connecting Guillain-Barré syndrome (GBS) cases to prior M. pneumoniae infections represent a concern for exploiting such a chassis. Galactolipids, especially galactocerebroside (GalCer), are considered the most likely M. pneumoniae antigens triggering autoimmune responses associated with GBS development. In this work, we generated different strains lacking genes involved in galactolipids biosynthesis. Glycolipid profiling of the strains demonstrated that some mutants show a complete lack of galactolipids. Cross-reactivity assays with sera from GBS patients with prior M. pneumoniae infection showed that certain engineered strains exhibit reduced antibody recognition. However, correlation analyses of these results with the glycolipid profile of the engineered strains suggest that other factors different from GalCer contribute to sera recognition, including total ceramide levels, dihexosylceramide (DHCer), and diglycosyldiacylglycerol (DGDAG). Finally, we discuss the best candidate strains as potential GBS-free Mycoplasma chassis., Competing Interests: Declaration of competing interest The results published in this article are covered by patents PCT/EP2021/057122 and US2023/0310564 A1(licensed to Pulmobiotics S.L). L.S. and M.L.-S. are shareholders of Pulmobiotics S.L.. C.P.-L., R.M., and M.L.-S. are employees and have stock options of Pulmobiotics S.L. The remaining authors declare no competing interests., (Copyright © 2024 The Authors. Published by Elsevier Masson SAS.. All rights reserved.)

The regulation of exon inclusion through alternative splicing tunes the cell's behavior by increasing the functional diversity of the transcriptome and the proteome. Splicing factors work in concert to generate gene isoform pools that contribute to cell phenotypes yet their activity is controlled by multiple regulatory and signaling layers. This hinders identification of functional, phenotype-specific splicing factors using traditional single-omic measurements, such as their mutational state or expression. To address this challenge, we propose repurposing the virtual inference of protein activity by enriched regulon analysis (VIPER) to measure splicing factor activity solely from their downstream exon transcriptomic inclusion signatures. This approach is effective in assessing the effect of co-occurring splicing factor perturbations, as well as their post-translational regulation. As proof of concept, we dissect recurrent splicing factor programs underlying tumorigenesis including aberrantly activated factors acting as oncogenes and inactivated ones acting as tumor suppressors, which are undetectable by more conventional methodologies. Activation and inactivation of these cancer splicing programs effectively stratifies overall survival, as well as cancer hallmarks such as proliferation and immune evasion. Altogether, repurposing network-based inference of protein activity for splicing factor networks distills common, functionally relevant splicing programs in otherwise heterogeneous molecular contexts., Competing Interests: CONFLICTS OF INTEREST Dr. Califano is founder, equity holder, and consultant of DarwinHealth Inc., a company that has licensed some of the algorithms used in this manuscript from Columbia University. Columbia University is also an equity holder in DarwinHealth Inc. The rest of authors declare no conflicts of interest.

Identifying open reading frames (ORFs) being translated is not a trivial task. ProTInSeq is a technique designed to characterize proteomes by sequencing transposon insertions engineered to express a selection marker when they occur in-frame within a protein-coding gene. In the bacterium Mycoplasma pneumoniae, ProTInSeq identifies 83% of its annotated proteins, along with 5 proteins and 153 small ORF-encoded proteins (SEPs; ≤100 aa) that were not previously annotated. Moreover, ProTInSeq can be utilized for detecting translational noise, as well as for relative quantification and transmembrane topology estimation of fitness and non-essential proteins. By integrating various identification approaches, the number of initially annotated SEPs in this bacterium increases from 27 to 329, with a quarter of them predicted to possess antimicrobial potential. Herein, we describe a methodology complementary to Ribo-Seq and mass spectroscopy that can identify SEPs while providing other insights in a proteome with a flexible and cost-effective DNA ultra-deep sequencing approach., (© 2024. The Author(s).)

The development of advanced genetic tools is boosting microbial engineering which can potentially tackle wide-ranging challenges currently faced by our society. Here we present SURE editing, a multi-recombinase engineering rationale combining oligonucleotide recombineering with the selective capacity of antibiotic resistance via transient insertion of selector plasmids. We test this method in Mycoplasma pneumoniae, a bacterium with a very inefficient native recombination machinery. Using SURE editing, we can seamlessly generate, in a single step, a wide variety of genome modifications at high efficiencies, including the largest possible deletion of this genome (30 Kb) and the targeted complementation of essential genes in the deletion of a region of interest. Additional steps can be taken to remove the selector plasmid from the edited area, to obtain markerless or even scarless edits. Of note, SURE editing is compatible with different site-specific recombinases for mediating transient plasmid integration. This battery of selector plasmids can be used to select different edits, regardless of the target sequence, which significantly reduces the cloning load associated to genome engineering projects. Given the proven functionality in several microorganisms of the machinery behind the SURE editing logic, this method is likely to represent a valuable advance for the synthetic biology field., (© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Background: Independent Component Analysis (ICA) allows the dissection of omic datasets into modules that help to interpret global molecular signatures. The inherent randomness of this algorithm can be overcome by clustering many iterations of ICA together to obtain robust components. Existing algorithms for robust ICA are dependent on the choice of clustering method and on computing a potentially biased and large Pearson distance matrix., Results: We present robustica, a Python-based package to compute robust independent components with a fully customizable clustering algorithm and distance metric. Here, we exploited its customizability to revisit and optimize robust ICA systematically. Of the 6 popular clustering algorithms considered, DBSCAN performed the best at clustering independent components across ICA iterations. To enable using Euclidean distances, we created a subroutine that infers and corrects the components' signs across ICA iterations. Our subroutine increased the resolution, robustness, and computational efficiency of the algorithm. Finally, we show the applicability of robustica by dissecting over 500 tumor samples from low-grade glioma (LGG) patients, where we define two new gene expression modules with key modulators of tumor progression upon IDH1 and TP53 mutagenesis., Conclusion: robustica brings precise, efficient, and customizable robust ICA into the Python toolbox. Through its customizability, we explored how different clustering algorithms and distance metrics can further optimize robust ICA. Then, we showcased how robustica can be used to discover gene modules associated with combinations of features of biological interest. Taken together, given the broad applicability of ICA for omic data analysis, we envision robustica will facilitate the seamless computation and integration of robust independent components in large pipelines., (© 2022. The Author(s).)

Retinal photoreceptors have a distinct transcriptomic profile compared to other neuronal subtypes, likely reflecting their unique cellular morphology and function in the detection of light stimuli by way of the ciliary outer segment. We discovered a layer of this molecular specialization by revealing that the vertebrate retina expresses the largest number of tissue-enriched microexons of all tissue types. A subset of these microexons is included exclusively in photoreceptor transcripts, particularly in genes involved in cilia biogenesis and vesicle-mediated transport. This microexon program is regulated by Srrm3 , a paralog of the neural microexon regulator Srrm4 . Despite the fact that both proteins positively regulate retina microexons in vitro, only Srrm3 is highly expressed in mature photoreceptors. Its deletion in zebrafish results in widespread down-regulation of microexon inclusion from early developmental stages, followed by other transcriptomic alterations, severe photoreceptor defects, and blindness. These results shed light on the transcriptomic specialization and functionality of photoreceptors, uncovering unique cell type-specific roles for Srrm3 and microexons with implications for retinal diseases.

Mycoplasmas have exceptionally streamlined genomes and are strongly adapted to their many hosts, which provide them with essential nutrients. Owing to their relative genomic simplicity, Mycoplasmas have been used to develop chassis for biotechnological applications. However, the dearth of robust and precise toolkits for genomic manipulation and tight regulation has hindered any substantial advance. Herein we describe the construction of a robust genetic toolkit for M. pneumoniae, and its successful deployment to engineer synthetic gene switches that control and limit Mycoplasma growth, for biosafety containment applications. We found these synthetic gene circuits to be stable and robust in the long-term, in the context of a minimal cell. With this work, we lay a foundation to develop viable and robust biosafety systems to exploit a synthetic Mycoplasma chassis for live attenuated vectors for therapeutic applications., (© 2022. The Author(s).)

The removal of unwanted genetic material is a key aspect in many synthetic biology efforts and often requires preliminary knowledge of which genomic regions are dispensable. Typically, these efforts are guided by transposon mutagenesis studies, coupled to deepsequencing (TnSeq) to identify insertion points and gene essentiality. However, epistatic interactions can cause unforeseen changes in essentiality after the deletion of a gene, leading to the redundancy of these essentiality maps. Here, we present LoxTnSeq, a new methodology to generate and catalogue libraries of genome reduction mutants. LoxTnSeq combines random integration of lox sites by transposon mutagenesis, and the generation of mutants via Cre recombinase, catalogued via deep sequencing. When LoxTnSeq was applied to the naturally genome reduced bacterium Mycoplasma pneumoniae, we obtained a mutant pool containing 285 unique deletions. These deletions spanned from > 50 bp to 28 Kb, which represents 21% of the total genome. LoxTnSeq also highlighted large regions of non-essential genes that could be removed simultaneously, and other non-essential regions that could not, providing a guide for future genome reductions., (© 2020 The Authors. Microbial Biotechnology published by Society for Applied Microbiology and John Wiley & Sons Ltd.)

Transposon sequencing is commonly applied for identifying the minimal set of genes required for cellular life; a major challenge in fields such as evolutionary or synthetic biology. However, the scientific community has no standards at the level of processing, treatment, curation and analysis of this kind data. In addition, we lack knowledge about artifactual signals and the requirements a dataset has to satisfy to allow accurate prediction. Here, we have developed FASTQINS, a pipeline for the detection of transposon insertions, and ANUBIS, a library of functions to evaluate and correct deviating factors known and uncharacterized until now. ANUBIS implements previously defined essentiality estimate models in addition to new approaches with advantages like not requiring a training set of genes to predict general essentiality. To highlight the applicability of these tools, and provide a set of recommendations on how to analyze transposon sequencing data, we performed a comprehensive study on artifacts corrections and essentiality estimation at a 1.5-bp resolution, in the genome-reduced bacterium Mycoplasma pneumoniae. We envision FASTQINS and ANUBIS to aid in the analysis of Tn-seq procedures and lead to the development of accurate genome essentiality estimates to guide applications such as designing live vaccines or growth optimization., (© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Here, we propose an approach to identify active metabolic pathways by integrating gene essentiality analysis and protein abundance. We use two bacterial species (Mycoplasma pneumoniae and Mycoplasma agalactiae) that share a high gene content similarity yet show significant metabolic differences. First, we build detailed metabolic maps of their carbon metabolism, the most striking difference being the absence of two key enzymes for glucose metabolism in M. agalactiae. We then determine carbon sources that allow growth in M. agalactiae, and we introduce glucose-dependent growth to show the functionality of its remaining glycolytic enzymes. By analyzing gene essentiality and performing quantitative proteomics, we can predict the active metabolic pathways connected to carbon metabolism and show significant differences in use and direction of key pathways despite sharing the large majority of genes. Gene essentiality combined with quantitative proteomics and metabolic maps can be used to determine activity and directionality of metabolic pathways., Competing Interests: Declaration of Interests The authors declare no competing interests., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Mycoplasmas are important model organisms for Systems and Synthetic Biology, and are pathogenic to a wide variety of species. Despite their relevance, many of the tools established for genome editing in other microorganisms are not available for Mycoplasmas. The Tn4001 transposon is the reference tool to work with these bacteria, but the transformation efficiencies (TEs) reported for the different species vary substantially. Here, we explore the mechanisms underlying these differences in four Mycoplasma species, Mycoplasma agalactiae, Mycoplasma feriruminatoris, Mycoplasma gallisepticum and Mycoplasma pneumoniae, selected for being representative members of each cluster of the Mycoplasma genus. We found that regulatory regions (RRs) driving the expression of the transposase and the antibiotic resistance marker have a major impact on the TEs. We then designed a synthetic RR termed SynMyco RR to control the expression of the key transposon vector elements. Using this synthetic RR, we were able to increase the TE for M. gallisepticum, M. feriruminatoris and M. agalactiae by 30-, 980- and 1036-fold, respectively. Finally, to illustrate the potential of this new transposon, we performed the first essentiality study in M. agalactiae, basing our study on more than 199,000 genome insertions., (© The Author(s) 2019. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.)

Background: Cancer is a rapidly evolving, multifactorial disease that accumulates numerous genetic and epigenetic alterations. This results in molecular and phenotypic heterogeneity within the tumor, the complexity of which is further amplified through specific interactions between cancer cells. We aimed to dissect the molecular mechanisms underlying the cooperation between different clones., Methods: We produced clonal cell lines derived from the MDA-MB-231 breast cancer cell line, using the UbC-StarTrack system, which allowed tracking of multiple clones by color: GFP C3, mKO E10 and Sapphire D7. Characterization of these clones was performed by growth rate, cell metabolic activity, wound healing, invasion assays and genetic and epigenetic arrays. Tumorigenicity was tested by orthotopic and intravenous injections. Clonal cooperation was evaluated by medium complementation, co-culture and co-injection assays., Results: Characterization of these clones in vitro revealed clear genetic and epigenetic differences that affected growth rate, cell metabolic activity, morphology and cytokine expression among cell lines. In vivo, all clonal cell lines were able to form tumors; however, injection of an equal mix of the different clones led to tumors with very few mKO E10 cells. Additionally, the mKO E10 clonal cell line showed a significant inability to form lung metastases. These results confirm that even in stable cell lines heterogeneity is present. In vitro, the complementation of growth medium with medium or exosomes from parental or clonal cell lines increased the growth rate of the other clones. Complementation assays, co-growth and co-injection of mKO E10 and GFP C3 clonal cell lines increased the efficiency of invasion and migration., Conclusions: These findings support a model where interplay between clones confers aggressiveness, and which may allow identification of the factors involved in cellular communication that could play a role in clonal cooperation and thus represent new targets for preventing tumor progression.

Identification of small open reading frames (smORFs) encoding small proteins (≤ 100 amino acids; SEPs) is a challenge in the fields of genome annotation and protein discovery. Here, by combining a novel bioinformatics tool (RanSEPs) with "-omics" approaches, we were able to describe 109 bacterial small ORFomes. Predictions were first validated by performing an exhaustive search of SEPs present in Mycoplasma pneumoniae proteome via mass spectrometry, which illustrated the limitations of shotgun approaches. Then, RanSEPs predictions were validated and compared with other tools using proteomic datasets from different bacterial species and SEPs from the literature. We found that up to 16 ± 9% of proteins in an organism could be classified as SEPs. Integration of RanSEPs predictions with transcriptomics data showed that some annotated non-coding RNAs could in fact encode for SEPs. A functional study of SEPs highlighted an enrichment in the membrane, translation, metabolism, and nucleotide-binding categories. Additionally, 9.7% of the SEPs included a N-terminus predicted signal peptide. We envision RanSEPs as a tool to unmask the hidden universe of small bacterial proteins., (© 2019 The Authors. Published under the terms of the CC BY 4.0 license.)

Transcription is a core process of bacterial physiology, and as such it must be tightly controlled, so that bacterial cells maintain steady levels of each RNA molecule in homeostasis and modify them in response to perturbations. The major regulators of transcription in bacteria (and in eukaryotes) are transcription factors. However, in genome-reduced bacteria, the limited number of these proteins is insufficient to explain the variety of responses shown upon changes in their environment. Thus, alternative regulators may play a central role in orchestrating RNA levels in these microorganisms. These alternative mechanisms rely on intrinsic features within DNA and RNA molecules, suggesting they are ancestral mechanisms shared among bacteria that could have an increased relevance on transcriptional regulation in minimal cells. In this review, we summarize the alternative elements that can regulate transcript abundance in genome-reduced bacteria and how they contribute to the RNA homeostasis at different levels., (Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Bacteria are needed for a vast range of biotechnological processes, which they carry out either as pure cultures or in association with other bacteria and/or fungi. The potential of bacteria as biofactories is hampered, though, by their limited mobility in solid or semisolid media such as agricultural or domestic waste. This work represents an attempt toward overcoming this limitation by associating bacterial biotechnological properties with the transport ability of the nematode Caenorhabditis elegans. We report here biofilm formation on C. elegans by engineered Escherichia coli expressing a Xhenorhabdus nematophila adhesion operon and induction of nematode social feeding behavior (clumping) through an E. coli-mediated iRNA blocking on the expression of FLP-21, a neuropeptide involved in worm solitary behavior.