ABC-HuMi: the Atlas of Biosynthetic Gene Clusters in the Human Microbiome.

The human microbiome has emerged as a rich source of diverse and bioactive natural products, harboring immense potential for therapeutic applications. To facilitate systematic exploration and analysis of its biosynthetic landscape, we present ABC-HuMi: the Atlas of Biosynthetic Gene Clusters (BGCs) in the Human Microbiome. ABC-HuMi integrates data from major human microbiome sequence databases and provides an expansive repository of BGCs compared to the limited coverage offered by existing resources. Employing state-of-the-art BGC prediction and analysis tools, our database ensures accurate annotation and enhanced prediction capabilities. ABC-HuMi empowers researchers with advanced browsing, filtering, and search functionality, enabling efficient exploration of the resource. At present, ABC-HuMi boasts a catalog of 19 218 representative BGCs derived from the human gut, oral, skin, respiratory and urogenital systems. By capturing the intricate biosynthetic potential across diverse human body sites, our database fosters profound insights into the molecular repertoire encoded within the human microbiome and offers a comprehensive resource for the discovery and characterization of novel bioactive compounds. The database is freely accessible at https://www.ccb.uni-saarland.de/abc_humi/.

HypoRiPPAtlas as an Atlas of hypothetical natural products for mass spectrometry database search.

Recent analyses of public microbial genomes have found over a million biosynthetic gene clusters, the natural products of the majority of which remain unknown. Additionally, GNPS harbors billions of mass spectra of natural products without known structures and biosynthetic genes. We bridge the gap between large-scale genome mining and mass spectral datasets for natural product discovery by developing HypoRiPPAtlas, an Atlas of hypothetical natural product structures, which is ready-to-use for in silico database search of tandem mass spectra. HypoRiPPAtlas is constructed by mining genomes using seq2ripp, a machine-learning tool for the prediction of ribosomally synthesized and post-translationally modified peptides (RiPPs). In HypoRiPPAtlas, we identify RiPPs in microbes and plants. HypoRiPPAtlas could be extended to other natural product classes in the future by implementing corresponding biosynthetic logic. This study paves the way for large-scale explorations of biosynthetic pathways and chemical structures of microbial and plant RiPP classes.

WebQUAST: online evaluation of genome assemblies.

Selecting proper genome assembly is key for downstream analysis in genomics studies. However, the availability of many genome assembly tools and the huge variety of their running parameters challenge this task. The existing online evaluation tools are limited to specific taxa or provide just a one-sided view on the assembly quality. We present WebQUAST, a web server for multifaceted quality assessment and comparison of genome assemblies based on the state-of-the-art QUAST tool. The server is freely available at https://www.ccb.uni-saarland.de/quast/. WebQUAST can handle an unlimited number of genome assemblies and evaluate them against a user-provided or pre-loaded reference genome or in a completely reference-free fashion. We demonstrate key WebQUAST features in three common evaluation scenarios: assembly of an unknown species, a model organism, and a close variant of it.

Imaging and Interventions for Lymphatic and Lymphatic-related Disorders.

The lymphatic system is critical in fluid balance homeostasis. Yet, until recently, lymphatic imaging has been outside of mainstream medicine due to a lack of robust imaging and interventional options. However, during the last 20 years, both clinical lymphatic imaging and interventions have shown dramatic advancement. The key to imaging advancement has been the interstitial delivery of contrast agents through lymphatic-rich tissues. These techniques include intranodal lymphangiography and dynamic contrast-enhanced MR lymphangiography. These methods provide the ability to image and recognize lymphatic anatomy and pathologic conditions. Percutaneous thoracic duct catheterization and embolization became the first widely accepted interventional technique for the management of chyle leaks. Advances in interstitial lymphatic embolization, as well as liver and mesenteric lymphatic interventions, have broadened the scope of possible lymphatic interventions. Also, recent techniques of lymphatic decompression allow for the treatment of a variety of lymphatic disorders. Finally, immunologic studies of central lymphatic fluid reveal the potential of lymphatic interventions on immunity. These advances herald an exciting new chapter for lymphatic imaging and interventions in the coming years.

NPvis: An Interactive Visualizer of Peptidic Natural Product-MS/MS Matches.

Peptidic natural products (PNPs) represent a medically important class of secondary metabolites that includes antibiotics, anti-inflammatory and antitumor agents. Advances in tandem mass spectra (MS/MS) acquisition and in silico database search methods have enabled high-throughput PNP discovery. However, the resulting spectra annotations are often error-prone and their validation remains a bottleneck. Here, we present NPvis, a visualizer suitable for the evaluation of PNP-MS/MS matches. The tool interactively maps annotated spectrum peaks to the corresponding PNP fragments and allows researchers to assess the match correctness. NPvis accounts for the wide chemical diversity of PNPs that prevents the use of the existing proteomics visualizers. Moreover, NPvis works even if the exact chemical structure of the matching PNP is unknown. The tool is available online and as a standalone application. We hope that it will benefit the community by streamlining PNP data analysis and validation.

Critical Assessment of Metagenome Interpretation: the second round of challenges.

Evaluating metagenomic software is key for optimizing metagenome interpretation and focus of the Initiative for the Critical Assessment of Metagenome Interpretation (CAMI). The CAMI II challenge engaged the community to assess methods on realistic and complex datasets with long- and short-read sequences, created computationally from around 1,700 new and known genomes, as well as 600 new plasmids and viruses. Here we analyze 5,002 results by 76 program versions. Substantial improvements were seen in assembly, some due to long-read data. Related strains still were challenging for assembly and genome recovery through binning, as was assembly quality for the latter. Profilers markedly matured, with taxon profilers and binners excelling at higher bacterial ranks, but underperforming for viruses and Archaea. Clinical pathogen detection results revealed a need to improve reproducibility. Runtime and memory usage analyses identified efficient programs, including top performers with other metrics. The results identify challenges and guide researchers in selecting methods for analyses.

Transarterial Embolization Modulates the Immune Response within Target and Nontarget Hepatocellular Carcinomas in a Rat Model.

Background Transarterial embolization (TAE) is the most common treatment for hepatocellular carcinoma (HCC); however, there remain limited data describing the influence of TAE on the tumor immune microenvironment. Purpose To characterize TAE-induced modulation of the tumor immune microenvironment in a rat model of HCC and identify factors that modulate this response. Materials and Methods TAE was performed on autochthonous HCCs induced in rats with use of diethylnitrosamine. CD3, CD4, CD8, and FOXP3 lymphocytes, as well as programmed cell death protein ligand-1 (PD-L1) expression, were examined in three cohorts: tumors from rats that did not undergo embolization (control), embolized tumors (target), and nonembolized tumors from rats that had a different target tumor embolized (nontarget). Differences in immune cell recruitment associated with embolic agent type (tris-acryl gelatin microspheres [TAGM] vs hydrogel embolics) and vascular location were examined in rat and human tissues. A generalized estimating equation model and t, Mann-Whitney U, and χ2 tests were used to compare groups. Results Cirrhosis-induced alterations in CD8, CD4, and CD25/CD4 lymphocytes were partially normalized following TAE (CD8: 38.4%, CD4: 57.6%, and CD25/CD4: 21.1% in embolized liver vs 47.7% [P = .02], 47.0% [P = .01], and 34.9% [P = .03], respectively, in cirrhotic liver [36.1%, 59.6%, and 4.6% in normal liver]). Embolized tumors had a greater number of CD3, CD4, and CD8 tumor-infiltrating lymphocytes relative to controls (191.4 cells/mm2 vs 106.7 cells/mm2 [P = .03]; 127.8 cells/mm2 vs 53.8 cells/mm2 [P < .001]; and 131.4 cells/mm2 vs 78.3 cells/mm2 [P = .01]) as well as a higher PD-L1 expression score (4.1 au vs 1.9 au [P < .001]). A greater number of CD3, CD4, and CD8 lymphocytes were found near TAGM versus hydrogel embolics (4.1 vs 2.0 [P = .003]; 3.7 vs 2.0 [P = .01]; and 2.2 vs 1.1 [P = .03], respectively). The number of lymphocytes adjacent to embolics differed based on vascular location (17.9 extravascular CD68+ peri-TAGM cells vs 7.0 intravascular [P < .001]; 6.4 extravascular CD68+ peri-hydrogel embolic cells vs 3.4 intravascular [P < .001]). Conclusion Transarterial embolization-induced dynamic alterations of the tumor immune microenvironment are influenced by underlying liver disease, embolic agent type, and vascular location. © RSNA, 2022 Online supplemental material is available for this article. See also the editorials by Kennedy et al and by White in this issue.

Nontraumatic Chylothorax and Chylopericardium: Diagnosis and Treatment Using an Algorithmic Approach Based on Novel Lymphatic Imaging.

Rationale: Outcomes of interventional lymphangiographic treatment of nontraumatic chylous pleural effusions using traditional approaches have been highly variable. Recent advances in lymphatic imaging have revealed variations in underlying pathophysiology, enabling improved targeting of therapeutic interventions. Objectives: To assess outcomes of an algorithm for management of nontraumatic chylous pleural effusions based on advanced magnetic resonance (MR) identification of various abnormalities in the thoracoabdominal lymphatic network that give rise to chylothorax. Methods: Novel lymphatic MR imaging was performed in 52 patients aged 11-89 years. Three distinct pathophysiological patterns were found: 1) abnormal pulmonary lymphatic flow from the thoracic duct only; 2) abnormal pulmonary lymphatic flow from retroperitoneal lymphatic networks with or without involvement of the thoracic duct; and 3) chylous ascites presenting as chylous pleural effusion. Lymphatic interventions were individualized to the underlying pathophysiological patterns. Results: In 41/52 (79%) patients, imaging revealed abnormal pulmonary lymphatic flow from the thoracic duct and/or retroperitoneal lymphatic networks. Thoracic duct embolization and/or interstitial embolization of retroperitoneal lymphatic resulted in resolution of chylothorax in this group in 38/41 (93%) of those patients. Five patients experienced grade 1 or 2 complications. One patient succumbed to postoperative stress-induced cardiomyopathy and pulmonary embolism. Chylous ascites was the cause of chylothorax in 11/52 (21%) patients. Eight chose to undergo interventions for chylous ascites with clinical success in 6/8 (75%). Conclusions: Application of magnetic resonance imaging-guided intervention algorithm resulted in successful control of nontraumatic chylothorax in 93% patients with abnormal pulmonary lymphatic flow. Appropriate treatment of chylous ascites presenting as a pleural effusion requires systematic evaluation and diagnosis prior to potential treatments.

NPOmix: A machine learning classifier to connect mass spectrometry fragmentation data to biosynthetic gene clusters.

Microbial specialized metabolites are an important source of and inspiration for many pharmaceuticals, biotechnological products and play key roles in ecological processes. Untargeted metabolomics using liquid chromatography coupled with tandem mass spectrometry is an efficient technique to access metabolites from fractions and even environmental crude extracts. Nevertheless, metabolomics is limited in predicting structures or bioactivities for cryptic metabolites. Efficiently linking the biosynthetic potential inferred from (meta)genomics to the specialized metabolome would accelerate drug discovery programs by allowing metabolomics to make use of genetic predictions. Here, we present a k-nearest neighbor classifier to systematically connect mass spectrometry fragmentation spectra to their corresponding biosynthetic gene clusters (independent of their chemical class). Our new pattern-based genome mining pipeline links biosynthetic genes to metabolites that they encode for, as detected via mass spectrometry from bacterial cultures or environmental microbiomes. Using paired datasets that include validated genes-mass spectral links from the Paired Omics Data Platform, we demonstrate this approach by automatically linking 18 previously known mass spectra (17 for which the biosynthesis gene clusters can be found at the MIBiG database plus palmyramide A) to their corresponding previously experimentally validated biosynthetic genes (e.g., via nuclear magnetic resonance or genetic engineering). We illustrated a computational example of how to use our Natural Products Mixed Omics (NPOmix) tool for siderophore mining that can be reproduced by the users. We conclude that NPOmix minimizes the need for culturing (it worked well on microbiomes) and facilitates specialized metabolite prioritization based on integrative omics mining.

Nerpa: A Tool for Discovering Biosynthetic Gene Clusters of Bacterial Nonribosomal Peptides.

Microbial natural products are a major source of bioactive compounds for drug discovery. Among these molecules, nonribosomal peptides (NRPs) represent a diverse class of natural products that include antibiotics, immunosuppressants, and anticancer agents. Recent breakthroughs in natural product discovery have revealed the chemical structure of several thousand NRPs. However, biosynthetic gene clusters (BGCs) encoding them are known only for a few hundred compounds. Here, we developed Nerpa, a computational method for the high-throughput discovery of novel BGCs responsible for producing known NRPs. After searching 13,399 representative bacterial genomes from the RefSeq repository against 8368 known NRPs, Nerpa linked 117 BGCs to their products. We further experimentally validated the predicted BGC of ngercheumicin from Photobacterium galatheae via mass spectrometry. Nerpa supports searching new genomes against thousands of known NRP structures, and novel molecular structures against tens of thousands of bacterial genomes. The availability of these tools can enhance our understanding of NRP synthesis and the function of their biosynthetic enzymes.

MolDiscovery: learning mass spectrometry fragmentation of small molecules.

Identification of small molecules is a critical task in various areas of life science. Recent advances in mass spectrometry have enabled the collection of tandem mass spectra of small molecules from hundreds of thousands of environments. To identify which molecules are present in a sample, one can search mass spectra collected from the sample against millions of molecular structures in small molecule databases. The existing approaches are based on chemistry domain knowledge, and they fail to explain many of the peaks in mass spectra of small molecules. Here, we present molDiscovery, a mass spectral database search method that improves both efficiency and accuracy of small molecule identification by learning a probabilistic model to match small molecules with their mass spectra. A search of over 8 million spectra from the Global Natural Product Social molecular networking infrastructure shows that molDiscovery correctly identify six times more unique small molecules than previous methods.

Integrating genomics and metabolomics for scalable non-ribosomal peptide discovery.

Non-Ribosomal Peptides (NRPs) represent a biomedically important class of natural products that include a multitude of antibiotics and other clinically used drugs. NRPs are not directly encoded in the genome but are instead produced by metabolic pathways encoded by biosynthetic gene clusters (BGCs). Since the existing genome mining tools predict many putative NRPs synthesized by a given BGC, it remains unclear which of these putative NRPs are correct and how to identify post-assembly modifications of amino acids in these NRPs in a blind mode, without knowing which modifications exist in the sample. To address this challenge, here we report NRPminer, a modification-tolerant tool for NRP discovery from large (meta)genomic and mass spectrometry datasets. We show that NRPminer is able to identify many NRPs from different environments, including four previously unreported NRP families from soil-associated microbes and NRPs from human microbiota. Furthermore, in this work we demonstrate the anti-parasitic activities and the structure of two of these NRP families using direct bioactivity screening and nuclear magnetic resonance spectrometry, illustrating the power of NRPminer for discovering bioactive NRPs.

Lymphatic Interventional Treatment for Chyluria via Retrograde Thoracic Duct Access.

Chyluria is the leakage of intestinal lymph (chyle) into the urine. Novel lymphatic intervention techniques, such as interstitial lymphatic embolization, proved to be a useful treatment option for chyluria. However, one of the challenges of this approach is the difficulty in identifying connections between the lymphatic system and kidney collecting system. Here, embolization of the abnormal lymphatic connection through retrograde thoracic duct access in 3 chyluria patients is introduced.

Tutorial: assessing metagenomics software with the CAMI benchmarking toolkit.

Computational methods are key in microbiome research, and obtaining a quantitative and unbiased performance estimate is important for method developers and applied researchers. For meaningful comparisons between methods, to identify best practices and common use cases, and to reduce overhead in benchmarking, it is necessary to have standardized datasets, procedures and metrics for evaluation. In this tutorial, we describe emerging standards in computational meta-omics benchmarking derived and agreed upon by a larger community of researchers. Specifically, we outline recent efforts by the Critical Assessment of Metagenome Interpretation (CAMI) initiative, which supplies method developers and applied researchers with exhaustive quantitative data about software performance in realistic scenarios and organizes community-driven benchmarking challenges. We explain the most relevant evaluation metrics for assessing metagenome assembly, binning and profiling results, and provide step-by-step instructions on how to generate them. The instructions use simulated mouse gut metagenome data released in preparation for the second round of CAMI challenges and showcase the use of a repository of tool results for CAMI datasets. This tutorial will serve as a reference for the community and facilitate informative and reproducible benchmarking in microbiome research.

A Multi-Omics Characterization of the Natural Product Potential of Tropical Filamentous Marine Cyanobacteria.

Microbial natural products are important for the understanding of microbial interactions, chemical defense and communication, and have also served as an inspirational source for numerous pharmaceutical drugs. Tropical marine cyanobacteria have been highlighted as a great source of new natural products, however, few reports have appeared wherein a multi-omics approach has been used to study their natural products potential (i.e., reports are often focused on an individual natural product and its biosynthesis). This study focuses on describing the natural product genetic potential as well as the expressed natural product molecules in benthic tropical cyanobacteria. We collected from several sites around the world and sequenced the genomes of 24 tropical filamentous marine cyanobacteria. The informatics program antiSMASH was used to annotate the major classes of gene clusters. BiG-SCAPE phylum-wide analysis revealed the most promising strains for natural product discovery among these cyanobacteria. LCMS/MS-based metabolomics highlighted the most abundant molecules and molecular classes among 10 of these marine cyanobacterial samples. We observed that despite many genes encoding for peptidic natural products, peptides were not as abundant as lipids and lipopeptides in the chemical extracts. Our results highlight a number of highly interesting biosynthetic gene clusters for genome mining among these cyanobacterial samples.

metaFlye: scalable long-read metagenome assembly using repeat graphs.

Long-read sequencing technologies have substantially improved the assemblies of many isolate bacterial genomes as compared to fragmented short-read assemblies. However, assembling complex metagenomic datasets remains difficult even for state-of-the-art long-read assemblers. Here we present metaFlye, which addresses important long-read metagenomic assembly challenges, such as uneven bacterial composition and intra-species heterogeneity. First, we benchmarked metaFlye using simulated and mock bacterial communities and show that it consistently produces assemblies with better completeness and contiguity than state-of-the-art long-read assemblers. Second, we performed long-read sequencing of the sheep microbiome and applied metaFlye to reconstruct 63 complete or nearly complete bacterial genomes within single contigs. Finally, we show that long-read assembly of human microbiomes enables the discovery of full-length biosynthetic gene clusters that encode biomedically important natural products.

Feature-based molecular networking in the GNPS analysis environment.

Molecular networking has become a key method to visualize and annotate the chemical space in non-targeted mass spectrometry data. We present feature-based molecular networking (FBMN) as an analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure that builds on chromatographic feature detection and alignment tools. FBMN enables quantitative analysis and resolution of isomers, including from ion mobility spectrometry.

TandemTools: mapping long reads and assessing/improving assembly quality in extra-long tandem repeats.

MOTIVATION: Extra-long tandem repeats (ETRs) are widespread in eukaryotic genomes and play an important role in fundamental cellular processes, such as chromosome segregation. Although emerging long-read technologies have enabled ETR assemblies, the accuracy of such assemblies is difficult to evaluate since there are no tools for their quality assessment. Moreover, since the mapping of error-prone reads to ETRs remains an open problem, it is not clear how to polish draft ETR assemblies. RESULTS: To address these problems, we developed the TandemTools software that includes the TandemMapper tool for mapping reads to ETRs and the TandemQUAST tool for polishing ETR assemblies and their quality assessment. We demonstrate that TandemTools not only reveals errors in ETR assemblies but also improves the recently generated assemblies of human centromeres. AVAILABILITY AND IMPLEMENTATION: https://github.com/ablab/TandemTools. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.