Advances and Challenges in Fluorescence in situ Hybridization for Visualizing Fungal Endobacteria.

Several bacteria have long been known to interact intimately with fungi, but molecular approaches have only recently uncovered how cosmopolitan these interactions are in nature. Currently, bacterial-fungal interactions (BFI) are inferred based on patterns of co-occurrence in amplicon sequencing investigations. However, determining the nature of these interactions, whether the bacteria are internally or externally associated, remains a grand challenge in BFI research. Fluorescence in situ hybridization (FISH) is a robust method that targets unique sequences of interest which can be employed for visualizing intra-hyphal targets, such as mitochondrial organelles or, as in this study, bacteria. We evaluate the challenges and employable strategies to resolve intra-hyphal BFI to address pertinent criteria in BFI research, such as culturing media, spatial distribution of bacteria, and abundance of bacterial 16S rRNA copies for fluorescent labeling. While these experimental factors influence labeling and detection of endobacteria, we demonstrate how to overcome these challenges thorough permeabilization, appropriate media choice, and targeted amplification using hybridization chain reaction FISH. Such microscopy imaging approaches can now be utilized by the broader research community to complement sequence-based investigations and provide more conclusive evidence on the nature of specific bacterial-fungal relationships.

ClpP inhibitors are produced by a widespread family of bacterial gene clusters.

The caseinolytic protease (ClpP) is part of a highly conserved proteolytic complex whose disruption can lead to antibacterial activity but for which few specific inhibitors have been discovered. Specialized metabolites produced by bacteria have been shaped by evolution for specific functions, making them a potential source of selective ClpP inhibitors. Here, we describe a target-directed genome mining strategy for discovering ClpP-interacting compounds by searching for biosynthetic gene clusters that contain duplicated copies of ClpP as putative antibiotic resistance genes. We identify a widespread family of ClpP-associated clusters that are known to produce pyrrolizidine alkaloids but whose connection to ClpP has never been made. We show that previously characterized molecules do not affect ClpP function but are shunt metabolites derived from the genuine product of these gene clusters, a reactive covalent ClpP inhibitor. Focusing on one such cryptic gene cluster from Streptomyces cattleya, we identify the relevant inhibitor, which we name clipibicyclene, and show that it potently and selectively inactivates ClpP. Finally, we solve the crystal structure of clipibicyclene-modified Escherichia coli ClpP. Clipibicyclene's discovery reveals the authentic function of a family of natural products whose specificity for ClpP and abundance in nature illuminate the role of eco-evolutionary forces during bacterial competition.

Laboratory-Generated DNA Can Cause Anomalous Pathogen Diagnostic Test Results.

The coronavirus disease 2019 (COVID-19) pandemic has brought about the unprecedented expansion of highly sensitive molecular diagnostics as a primary infection control strategy. At the same time, many laboratories have shifted focus to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) research and diagnostic development, leading to large-scale production of SARS-CoV-2 nucleic acids that can interfere with these tests. We have identified multiple instances, in independent laboratories, in which nucleic acids generated in research settings are suspected to have caused researchers to test positive for SARS-CoV-2 in surveillance testing. In some cases, the affected individuals did not work directly with these nucleic acids but were exposed via a contaminated surface or object. Though researchers have long been vigilant of DNA contaminants, the transfer of these contaminants to SARS-CoV-2 testing samples can result in anomalous test results. The impact of these incidents stretches into the public sphere, placing additional burdens on public health resources, placing affected researchers and their contacts in isolation and quarantine, removing them from the testing pool for 3 months, and carrying the potential to trigger shutdowns of classrooms and workplaces. We report our observations as a call for increased stewardship over nucleic acids with the potential to impact both the use and development of diagnostics. IMPORTANCE To meet the challenges imposed by the COVID-19 pandemic, research laboratories shifted their focus and clinical diagnostic laboratories developed and utilized new assays. Nucleic acid-based testing became widespread and, for the first time, was used as a prophylactic measure. We report 15 cases of researchers at two institutes testing positive for SARS-CoV-2 on routine surveillance tests, in the absence of any symptoms or transmission. These researchers were likely contaminated with nonhazardous nucleic acids generated in the laboratory in the course of developing new SARS-CoV-2 diagnostics. These contaminating nucleic acids were persistent and widespread throughout the laboratory. We report these findings as a cautionary tale to those working with nucleic acids used in diagnostic testing and as a call for careful stewardship of diagnostically relevant molecules. Our conclusions are especially relevant as at-home COVID-19 testing gains traction in the marketplace and these amplicons may impact on the general public.

Barcoded oligonucleotides ligated on RNA amplified for multiplexed and parallel in situ analyses.

We present barcoded oligonucleotides ligated on RNA amplified for multiplexed and parallel insitu analyses (BOLORAMIS), a reverse transcription-free method for spatially-resolved, targeted, in situ RNA identification of single or multiple targets. BOLORAMIS was demonstrated on a range of cell types and human cerebral organoids. Singleplex experiments to detect coding and non-coding RNAs in human iPSCs showed a stem-cell signature pattern. Specificity of BOLORAMIS was found to be 92% as illustrated by a clear distinction between human and mouse housekeeping genes in a co-culture system, as well as by recapitulation of subcellular localization of lncRNA MALAT1. Sensitivity of BOLORAMIS was quantified by comparing with single molecule FISH experiments and found to be 11%, 12% and 35% for GAPDH, TFRC and POLR2A, respectively. To demonstrate BOLORAMIS for multiplexed gene analysis, we targeted 96 mRNAs within a co-culture of iNGN neurons and HMC3 human microglial cells. We used fluorescence in situ sequencing to detect error-robust 8-base barcodes associated with each of these genes. We then used this data to uncover the spatial relationship among cells and transcripts by performing single-cell clustering and gene-gene proximity analyses. We anticipate the BOLORAMIS technology for in situ RNA detection to find applications in basic and translational research.

CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database.

The Comprehensive Antibiotic Resistance Database (CARD; https://card.mcmaster.ca) is a curated resource providing reference DNA and protein sequences, detection models and bioinformatics tools on the molecular basis of bacterial antimicrobial resistance (AMR). CARD focuses on providing high-quality reference data and molecular sequences within a controlled vocabulary, the Antibiotic Resistance Ontology (ARO), designed by the CARD biocuration team to integrate with software development efforts for resistome analysis and prediction, such as CARD's Resistance Gene Identifier (RGI) software. Since 2017, CARD has expanded through extensive curation of reference sequences, revision of the ontological structure, curation of over 500 new AMR detection models, development of a new classification paradigm and expansion of analytical tools. Most notably, a new Resistomes & Variants module provides analysis and statistical summary of in silico predicted resistance variants from 82 pathogens and over 100 000 genomes. By adding these resistance variants to CARD, we are able to summarize predicted resistance using the information included in CARD, identify trends in AMR mobility and determine previously undescribed and novel resistance variants. Here, we describe updates and recent expansions to CARD and its biocuration process, including new resources for community biocuration of AMR molecular reference data.

Hidden antibiotics in actinomycetes can be identified by inactivation of gene clusters for common antibiotics.

Actinobacteria, which are one of the largest bacterial phyla and comprise between 13 and 30% of the soil microbiota, are the main source of antibiotic classes in clinical use1. During screens for antimicrobials, as many as 50% of actinomycete strains are discarded because they produce a known antibiotic (Supplementary Fig. 1) (ref. 2). Despite each strain likely having the capacity to produce many compounds, strains are abandoned because the already characterized antibiotic could interfere with screening for, or purification of, newly discovered compounds3. We applied CRISPR-Cas9 genome engineering to knockout genes encoding two of the most frequently rediscovered antibiotics, streptothricin or streptomycin, in 11 actinomycete strains. We report that this simple approach led to production of different antibiotics that were otherwise masked. We were able to rapidly discover rare and previously unknown variants of antibiotics including thiolactomycin, amicetin, phenanthroviridin and 5-chloro-3-formylindole. This strategy could be applied to existing strain collections to realize their biosynthetic potential.

Trichlorination of a Teicoplanin-Type Glycopeptide Antibiotic by the Halogenase StaI Evades Resistance.

Glycopeptide antibiotics (GPAs) include clinically important drugs used for the treatment of infections caused by Gram-positive pathogens. These antibiotics are specialized metabolites produced by several genera of actinomycete bacteria. While many GPAs are highly chemically modified, A47934 is a relatively unadorned GPA lacking sugar or acyl modifications, common to other members of the class, but which is chlorinated at three distinct sites. The biosynthesis of A47934 is encoded by a 68-kb gene cluster in Streptomyces toyocaensis NRRL 15009. The cluster includes all necessary genes for the synthesis of A47934, including two predicted halogenase genes, staI and staK In this study, we report that only one of the halogenase genes, staI, is necessary and essential for A47934 biosynthesis. Chlorination of the A47934 scaffold is important for antibiotic activity, as assessed by binding affinity for the target N-acyl-d-Ala-d-Ala. Surprisingly, chlorination is also vital to avoid activation of enterococcal and Streptomyces VanB-type GPA resistance through induction of resistance genes. Phenotypic assays showed stronger induction of GPA resistance by the dechlorinated compared to the chlorinated GPA. Correspondingly, the relative expression of the enterococcal vanA resistance gene was shown to be increased by the dechlorinated compared to the chlorinated compound. These results provide insight into the biosynthesis of GPAs and the biological function of GPA chlorination for this medically important class of antibiotic.

The evolution of substrate discrimination in macrolide antibiotic resistance enzymes.

The production of antibiotics by microbes in the environment and their use in medicine and agriculture select for existing and emerging resistance. To address this inevitability, prudent development of antibiotic drugs requires careful consideration of resistance evolution. Here, we identify the molecular basis for expanded substrate specificity in MphI, a macrolide kinase (Mph) that does not confer resistance to erythromycin, in contrast to other known Mphs. Using a combination of phylogenetics, drug-resistance phenotypes, and in vitro enzyme assays, we find that MphI and MphK phosphorylate erythromycin poorly resulting in an antibiotic-sensitive phenotype. Using likelihood reconstruction of ancestral sequences and site-saturation combinatorial mutagenesis, supported by Mph crystal structures, we determine that two non-obvious mutations in combination expand the substrate range. This approach should be applicable for studying the functional evolution of any antibiotic resistance enzyme and for evaluating the evolvability of resistance enzymes to new generations of antibiotic scaffolds.

The complex resistomes of Paenibacillaceae reflect diverse antibiotic chemical ecologies.

The ecology of antibiotic resistance involves the interplay of a long natural history of antibiotic production in the environment, and the modern selection of resistance in pathogens through human use of these drugs. Important components of the resistome are intrinsic resistance genes of environmental bacteria, evolved and acquired over millennia, and their mobilization, which drives dissemination in pathogens. Understanding the dynamics and evolution of resistance across bacterial taxa is essential to address the current crisis in drug-resistant infections. Here we report the exploration of antibiotic resistance in the Paenibacillaceae prompted by our discovery of an ancient intrinsic resistome in Paenibacillus sp. LC231, recovered from the isolated Lechuguilla cave environment. Using biochemical and gene expression analysis, we have mined the resistome of the second member of the Paenibacillaceae family, Brevibacillus brevis VM4, which produces several antimicrobial secondary metabolites. Using phylogenomics, we show that Paenibacillaceae resistomes are in flux, evolve mostly independent of secondary metabolite biosynthetic diversity, and are characterized by cryptic, redundant, pseudoparalogous, and orthologous genes. We find that in contrast to pathogens, mobile genetic elements are not significantly responsible for resistome remodeling. This offers divergent modes of resistome development in pathogens and environmental bacteria.

A Common Platform for Antibiotic Dereplication and Adjuvant Discovery.

Solving the antibiotic resistance crisis requires the discovery of new antimicrobial drugs and the preservation of existing ones. The discovery of inhibitors of antibiotic resistance, antibiotic adjuvants, is a proven example of the latter. A major difficulty in identifying new antibiotics is the frequent rediscovery of known compounds, necessitating laborious "dereplication" to identify novel chemical entities. We have developed an antibiotic resistance platform (ARP) that can be used for both the identification of antibiotic adjuvants and for antibiotic dereplication. The ARP is a cell-based array of mechanistically distinct individual resistance elements in an identical genetic background. In dereplication mode, we demonstrate the rapid identification, and thus discrimination, of common antibiotics. In adjuvant discovery mode, we show that the ARP can be harnessed in screens to identify inhibitors of resistance. The ARP is therefore a powerful tool that has broad application in confronting the resistance crisis.

CARD 2017: expansion and model-centric curation of the comprehensive antibiotic resistance database.

The Comprehensive Antibiotic Resistance Database (CARD; http://arpcard.mcmaster.ca) is a manually curated resource containing high quality reference data on the molecular basis of antimicrobial resistance (AMR), with an emphasis on the genes, proteins and mutations involved in AMR. CARD is ontologically structured, model centric, and spans the breadth of AMR drug classes and resistance mechanisms, including intrinsic, mutation-driven and acquired resistance. It is built upon the Antibiotic Resistance Ontology (ARO), a custom built, interconnected and hierarchical controlled vocabulary allowing advanced data sharing and organization. Its design allows the development of novel genome analysis tools, such as the Resistance Gene Identifier (RGI) for resistome prediction from raw genome sequence. Recent improvements include extensive curation of additional reference sequences and mutations, development of a unique Model Ontology and accompanying AMR detection models to power sequence analysis, new visualization tools, and expansion of the RGI for detection of emergent AMR threats. CARD curation is updated monthly based on an interplay of manual literature curation, computational text mining, and genome analysis.

A diverse intrinsic antibiotic resistome from a cave bacterium.

Antibiotic resistance is ancient and widespread in environmental bacteria. These are therefore reservoirs of resistance elements and reflective of the natural history of antibiotics and resistance. In a previous study, we discovered that multi-drug resistance is common in bacteria isolated from Lechuguilla Cave, an underground ecosystem that has been isolated from the surface for over 4 Myr. Here we use whole-genome sequencing, functional genomics and biochemical assays to reveal the intrinsic resistome of Paenibacillus sp. LC231, a cave bacterial isolate that is resistant to most clinically used antibiotics. We systematically link resistance phenotype to genotype and in doing so, identify 18 chromosomal resistance elements, including five determinants without characterized homologues and three mechanisms not previously shown to be involved in antibiotic resistance. A resistome comparison across related surface Paenibacillus affirms the conservation of resistance over millions of years and establishes the longevity of these genes in this genus.

Evolving medicinal chemistry strategies in antibiotic discovery.

Chemical modification of synthetic or natural product antibiotic scaffolds to expand potency and spectrum and to bypass mechanisms of resistance has dominated antibiotic drug discovery and proven immensely successful. However, the inexorable evolution of drug resistance coupled with a drought in innovation in antibiotic discovery contribute to a dearth of new drugs entering to market. Better understanding of the physicochemical properties of antibiotic chemical space is required to inform new antibiotic discovery. Innovations such as the development of antibiotic adjuvants to preserve efficacy of existing drugs together with expanding antibiotic chemical diversity through synthetic biology or new techniques to mine antibiotic producing organisms, are required to bridge the growing gap between the need for new drugs and their discovery.

The comprehensive antibiotic resistance database.

The field of antibiotic drug discovery and the monitoring of new antibiotic resistance elements have yet to fully exploit the power of the genome revolution. Despite the fact that the first genomes sequenced of free living organisms were those of bacteria, there have been few specialized bioinformatic tools developed to mine the growing amount of genomic data associated with pathogens. In particular, there are few tools to study the genetics and genomics of antibiotic resistance and how it impacts bacterial populations, ecology, and the clinic. We have initiated development of such tools in the form of the Comprehensive Antibiotic Research Database (CARD; http://arpcard.mcmaster.ca). The CARD integrates disparate molecular and sequence data, provides a unique organizing principle in the form of the Antibiotic Resistance Ontology (ARO), and can quickly identify putative antibiotic resistance genes in new unannotated genome sequences. This unique platform provides an informatic tool that bridges antibiotic resistance concerns in health care, agriculture, and the environment.