Protein-encoding circular RNAs (circRNAs) are newly identified RNA molecules characterized by intense interaction with translating ribosome. Emerging evidence has implicated physiological and pathological significance of these non-canonical RNAs, yet a large body of them remains unidentified. Due to limited tools at hand, we developed CircProPlus, an automated computational pipeline for de novo detection of translated circRNAs. In comparison to previously established CircPro, CircProPlus adjusts the overall workflow and integrates more robust implements for achieving easier accessibility, higher flexibility and productivity. In present study, we tested the performance of CircProPlus when using different circRNA-detecting implements (i.e., CIRI2, CirComPara2) in the evaluation of coding ability of circRNAs. Results showed that CirComPara2, a state-of-the-art algorithm, consistently outperformed CIRI2 when coupled with CircProPlus in testing real data collected from different RNA libraries and species, which highlighted its potency in data mining of circRNAs with protein-coding potential.

Amplicon sequencing has long served as a robust method for characterising microbial communities, and despite inherent resolution limitations, it remains a preferred technique, offering cost- and time-effective insights into bacterial compositions. Here, we introduce ONT-AmpSeq, a user-friendly pipeline designed for processing amplicon sequencing data generated from Oxford Nanopore Technology (ONT) devices. Our pipeline enables efficient creation of taxonomically annotated operational taxonomic unit (OTU) tables from ONT sequencing data, with the flexibility to multiplex amplicons on the same barcode. The pipeline encompasses six main steps-statistics, quality filtering, alignment, clustering, polishing, and taxonomic classification-integrating various state-of-the-art software tools. We provide a detailed description of each step, along with performance tests and robustness evaluations using both test data and a ZymoBIOMICS® Microbial Community Standard mock community dataset. Our results demonstrate the ability of ONT-AmpSeq to effectively process ONT amplicon data, offering valuable insights into microbial community composition. Additionally, we discuss the influence of polishing tools on taxonomic insight and the impact of taxonomic annotation methods on the derived microbial composition. Overall, ONT-AmpSeq represents a comprehensive solution for analysing ONT amplicon sequencing data, facilitating streamlined and reliable microbial community analysis. The pipeline, along with test data, is freely available for public use.

Multiplex, randomized CRISPR interference sequencing (MuRCiS) allows for the simultaneous identification of multiple gene knockouts that together influence microbial processes. Here, we report on an updated analysis tool called Auto-MuRCiS that utilizes Docker to make the analysis of these data rapid and more user-friendly.

The current 2019-2021 marine pharmacology literature review provides a continuation of previous reviews covering the period 1998 to 2018. Preclinical marine pharmacology research during 2019-2021 was published by researchers in 42 countries and contributed novel mechanism-of-action pharmacology for 171 structurally characterized marine compounds. The peer-reviewed marine natural product pharmacology literature reported antibacterial, antifungal, antiprotozoal, antituberculosis, and antiviral mechanism-of-action studies for 49 compounds, 87 compounds with antidiabetic and anti-inflammatory activities that also affected the immune and nervous system, while another group of 51 compounds demonstrated novel miscellaneous mechanisms of action, which upon further investigation, may contribute to several pharmacological classes. Thus, in 2019-2021, a very active preclinical marine natural product pharmacology pipeline provided novel mechanisms of action as well as new lead chemistry for the clinical marine pharmaceutical pipeline targeting the therapy of several disease categories.

BACKGROUND: The flow diversion treatment of aneurysms located distal to the Circle of Willis has recently increased in frequency. We conducted a systematic review and meta-analysis of the clinical and radiological outcomes of flow diverter (FD) embolization in treating M1 aneurysms.
METHODS: PubMed, Web of Science, Ovid Medline, Ovid Embase, and Scopus were searched up to May 2024 using the Nested Knowledge platform. We included studies assessing the long-term clinical and radiological outcomes for M1 aneurysms. Results of FDs classified as Pipeline Embolization Devices (PED) versus other types of FDs. Angiographic occlusion rates, ischemic and hemorrhagic complications, and favorable clinic outcomes were included. All data were analyzed using R software version 4.2.2.
RESULTS: Thirteen studies with 112 total patients (58 patients for PED and 54 patients for other FD devices) were included in our meta-analysis. The overall adequate (complete + near-complete) occlusion rates were 85.1%. The complete occlusion rate was higher with PED than with other FD devices (72.9% PED and 41.6% for non-PED FDs, respectively, p-value <.01). The ischemic complications were 9.9% and 9.0% for the PED and non-PED groups, respectively (p-value = .89). The overall modified Rankin Scale 0-2 was 100% for the non-PED and 97.1% for the PED group (p-value = .51). In-stent stenosis rate was 7.5% for PED devices compared to 2.6% in the non-PED group (p-value = .35).
CONCLUSIONS: This relatively small meta-analysis showed high rates of adequate and complete occlusion in FD treatment of M1 segment aneurysms, with favorable safety profiles. PEDs were associated with higher rates of complete aneurysm occlusion compared to other types of FDs.

There is a lack of new antibiotics to combat drug-resistant bacterial infections that increasingly threaten global health. The current pipeline of clinical-stage antimicrobials is primarily populated by \"new and improved\" versions of existing antibiotic classes, supplemented by several novel chemical scaffolds that act on traditional targets. The lack of fresh chemotypes acting on previously unexploited targets (the \"holy grail\" for new antimicrobials due to their scarcity) is particularly unfortunate as these offer the greatest opportunity for innovative breakthroughs to overcome existing resistance. In recognition of their potential, this review focuses on this subset of high value antibiotics, providing chemical structures where available. This review focuses on candidates that have progressed to clinical trials, as well as selected examples of promising pioneering approaches in advanced stages of development, in order to stimulate additional research aimed at combating drug-resistant infections.

Antimicrobial resistance (AMR) is a major global health threat estimated to have caused the deaths of 1.27 million people in 2019, which is more than HIV/AIDS and malaria deaths combined. AMR also has significant consequences on the global economy. If not properly addressed, AMR could immensely impact the world\'s economy, further increasing the poverty burden in low- and middle-income countries. To mitigate the risk of a post-antibiotic society, where the ability to effectively treat common bacterial infections is being severely threatened, it is necessary to establish a continuous supply of new and novel antibacterial medicines. However, there are gaps in the current pipeline that will prove difficult to address, given the time required to develop new agents. To understand the status of upstream antibiotic development and the challenges faced by drug developers in the early development stage, the World Health Organization has regularly assessed the preclinical and clinical antibacterial development pipeline. The review identifies potential new classes of antibiotics or novel mechanisms of action that can better address resistant bacterial strains. This proactive approach is necessary to stay ahead of evolving resistance patterns and to support the availability of effective treatment options. This review examines the trends in preclinical development and attempts to identify gaps and potential opportunities to overcome the numerous hurdles in the early stages of the antibacterial research and development space.

BACKGROUND: Structural variations play an important role in bacterial genomes. They can mediate genome adaptation quickly in response to the external environment and thus can also play a role in antibiotic resistance. The detection of structural variations in bacteria is challenging, and the recognition of even small rearrangements can be important. Even though most detection tools are aimed at and benchmarked on eukaryotic genomes, they can also be used on prokaryotic genomes. The key features of detection are the ability to detect small rearrangements and support haploid genomes. Because of the limiting performance of a single detection tool, combining the detection abilities of multiple tools can lead to more robust results. There are already available workflows for structural variation detection for long-reads technologies and for the detection of single-nucleotide variation and indels, both aimed at bacteria. Yet we are unaware of structural variations detection workflows for the short-reads sequencing platform. Motivated by this gap we created our workflow. Further, we were interested in increasing the detection performance and providing more robust results.
RESULTS: We developed an open-source bioinformatics pipeline, ProcaryaSV, for the detection of structural variations in bacterial isolates from paired-end short sequencing reads. Multiple tools, starting with quality control and trimming of sequencing data, alignment to the reference genome, and multiple structural variation detection tools, are integrated. All the partial results are then processed and merged with an in-house merging algorithm. Compared with a single detection approach, ProcaryaSV has improved detection performance and is a reproducible easy-to-use tool.
CONCLUSIONS: The ProcaryaSV pipeline provides an integrative approach to structural variation detection from paired-end next-generation sequencing of bacterial samples. It can be easily installed and used on Linux machines. It is publicly available on GitHub at https://github.com/robinjugas/ProcaryaSV .

Microbial pangenome analysis identifies present or absent genes in prokaryotic genomes. However, current tools are limited when analyzing species with higher sequence diversity or higher taxonomic orders such as genera or families. The Roary ILP Bacterial core Annotation Pipeline (RIBAP) uses an integer linear programming approach to refine gene clusters predicted by Roary for identifying core genes. RIBAP successfully handles the complexity and diversity of Chlamydia, Klebsiella, Brucella, and Enterococcus genomes, outperforming other established and recent pangenome tools for identifying all-encompassing core genes at the genus level. RIBAP is a freely available Nextflow pipeline at github.com/hoelzer-lab/ribap and zenodo.org/doi/10.5281/zenodo.10890871.

UNASSIGNED: Neoantigen targeting therapies including personalized vaccines have shown promise in the treatment of cancers, particularly when used in combination with checkpoint blockade therapy. At least 100 clinical trials involving these therapies are underway globally. Accurate identification and prioritization of neoantigens is highly relevant to designing these trials, predicting treatment response, and understanding mechanisms of resistance. With the advent of massively parallel DNA and RNA sequencing technologies, it is now possible to computationally predict neoantigens based on patient-specific variant information. However, numerous factors must be considered when prioritizing neoantigens for use in personalized therapies. Complexities such as alternative transcript annotations, various binding, presentation and immunogenicity prediction algorithms, and variable peptide lengths/registers all potentially impact the neoantigen selection process. There has been a rapid development of computational tools that attempt to account for these complexities. While these tools generate numerous algorithmic predictions for neoantigen characterization, results from these pipelines are difficult to navigate and require extensive knowledge of the underlying tools for accurate interpretation. This often leads to over-simplification of pipeline outputs to make them tractable, for example limiting prediction to a single RNA isoform or only summarizing the top ranked of many possible peptide candidates. In addition to variant detection, gene expression and predicted peptide binding affinities, recent studies have also demonstrated the importance of mutation location, allele-specific anchor locations, and variation of T-cell response to long versus short peptides. Due to the intricate nature and number of salient neoantigen features, presenting all relevant information to facilitate candidate selection for downstream applications is a difficult challenge that current tools fail to address.
UNASSIGNED: We have created pVACview, the first interactive tool designed to aid in the prioritization and selection of neoantigen candidates for personalized neoantigen therapies including cancer vaccines. pVACview has a user-friendly and intuitive interface where users can upload, explore, select and export their neoantigen candidates. The tool allows users to visualize candidates across three different levels, including variant, transcript and peptide information.
UNASSIGNED: pVACview will allow researchers to analyze and prioritize neoantigen candidates with greater efficiency and accuracy in basic and translational settings The application is available as part of the pVACtools pipeline at pvactools.org and as an online server at pvacview.org.