Alarming antibody evasion properties of rising SARS-CoV-2 BQ and XBB subvariants.

The BQ and XBB subvariants of SARS-CoV-2 Omicron are now rapidly expanding, possibly due to altered antibody evasion properties deriving from their additional spike mutations. Here, we report that neutralization of BQ.1, BQ.1.1, XBB, and XBB.1 by sera from vaccinees and infected persons was markedly impaired, including sera from individuals boosted with a WA1/BA.5 bivalent mRNA vaccine. Titers against BQ and XBB subvariants were lower by 13- to 81-fold and 66- to 155-fold, respectively, far beyond what had been observed to date. Monoclonal antibodies capable of neutralizing the original Omicron variant were largely inactive against these new subvariants, and the responsible individual spike mutations were identified. These subvariants were found to have similar ACE2-binding affinities as their predecessors. Together, our findings indicate that BQ and XBB subvariants present serious threats to current COVID-19 vaccines, render inactive all authorized antibodies, and may have gained dominance in the population because of their advantage in evading antibodies.

Microbiota imbalance induced by dietary sugar disrupts immune-mediated protection from metabolic syndrome.

How intestinal microbes regulate metabolic syndrome is incompletely understood. We show that intestinal microbiota protects against development of obesity, metabolic syndrome, and pre-diabetic phenotypes by inducing commensal-specific Th17 cells. High-fat, high-sugar diet promoted metabolic disease by depleting Th17-inducing microbes, and recovery of commensal Th17 cells restored protection. Microbiota-induced Th17 cells afforded protection by regulating lipid absorption across intestinal epithelium in an IL-17-dependent manner. Diet-induced loss of protective Th17 cells was mediated by the presence of sugar. Eliminating sugar from high-fat diets protected mice from obesity and metabolic syndrome in a manner dependent on commensal-specific Th17 cells. Sugar and ILC3 promoted outgrowth of Faecalibaculum rodentium that displaced Th17-inducing microbiota. These results define dietary and microbiota factors posing risk for metabolic syndrome. They also define a microbiota-dependent mechanism for immuno-pathogenicity of dietary sugar and highlight an elaborate interaction between diet, microbiota, and intestinal immunity in regulation of metabolic disorders.

Intestinal microbiota-specific Th17 cells possess regulatory properties and suppress effector T cells via c-MAF and IL-10.

Commensal microbes induce cytokine-producing effector tissue-resident CD4+ T cells, but the function of these T cells in mucosal homeostasis is not well understood. Here, we report that commensal-specific intestinal Th17 cells possess an anti-inflammatory phenotype marked by expression of interleukin (IL)-10 and co-inhibitory receptors. The anti-inflammatory phenotype of gut-resident commensal-specific Th17 cells was driven by the transcription factor c-MAF. IL-10-producing commensal-specific Th17 cells were heterogeneous and derived from a TCF1+ gut-resident progenitor Th17 cell population. Th17 cells acquired IL-10 expression and anti-inflammatory phenotype in the small-intestinal lamina propria. IL-10 production by CD4+ T cells and IL-10 signaling in intestinal macrophages drove IL-10 expression by commensal-specific Th17 cells. Intestinal commensal-specific Th17 cells possessed immunoregulatory functions and curbed effector T cell activity in vitro and in vivo in an IL-10-dependent and c-MAF-dependent manner. Our results suggest that tissue-resident commensal-specific Th17 cells perform regulatory functions in mucosal homeostasis.

Antigenicity and receptor affinity of SARS-CoV-2 BA.2.86 spike.

A severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron subvariant, BA.2.86, has emerged and spread to numerous countries worldwide, raising alarm because its spike protein contains 34 additional mutations compared with its BA.2 predecessor1. We examined its antigenicity using human sera and monoclonal antibodies (mAbs). Reassuringly, BA.2.86 was no more resistant to human sera than the currently dominant XBB.1.5 and EG.5.1, indicating that the new subvariant would not have a growth advantage in this regard. Importantly, sera from people who had XBB breakthrough infection exhibited robust neutralizing activity against all viruses tested, suggesting that upcoming XBB.1.5 monovalent vaccines could confer added protection. Although BA.2.86 showed greater resistance to mAbs to subdomain 1 (SD1) and receptor-binding domain (RBD) class 2 and 3 epitopes, it was more sensitive to mAbs to class 1 and 4/1 epitopes in the 'inner face' of the RBD that is exposed only when this domain is in the 'up' position. We also identified six new spike mutations that mediate antibody resistance, including E554K that threatens SD1 mAbs in clinical development. The BA.2.86 spike also had a remarkably high receptor affinity. The ultimate trajectory of this new SARS-CoV-2 variant will soon be revealed by continuing surveillance, but its worldwide spread is worrisome.

Striking antibody evasion manifested by the Omicron variant of SARS-CoV-2.

The B.1.1.529/Omicron variant of SARS-CoV-2 was only recently detected in southern Africa, but its subsequent spread has been extensive, both regionally and globally1. It is expected to become dominant in the coming weeks2, probably due to enhanced transmissibility. A striking feature of this variant is the large number of spike mutations3 that pose a threat to the efficacy of current COVID-19 vaccines and antibody therapies4. This concern is amplified by the findings of our study. Here we found that B.1.1.529 is markedly resistant to neutralization by serum not only from patients who recovered from COVID-19, but also from individuals who were vaccinated with one of the four widely used COVID-19 vaccines. Even serum from individuals who were vaccinated and received a booster dose of mRNA-based vaccines exhibited substantially diminished neutralizing activity against B.1.1.529. By evaluating a panel of monoclonal antibodies against all known epitope clusters on the spike protein, we noted that the activity of 17 out of the 19 antibodies tested were either abolished or impaired, including ones that are currently authorized or approved for use in patients. Moreover, we also identified four new spike mutations (S371L, N440K, G446S and Q493R) that confer greater antibody resistance on B.1.1.529. The Omicron variant presents a serious threat to many existing COVID-19 vaccines and therapies, compelling the development of new interventions that anticipate the evolutionary trajectory of SARS-CoV-2.

Antibody evasion properties of SARS-CoV-2 Omicron sublineages.

The identification of the Omicron (B.1.1.529.1 or BA.1) variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Botswana in November 20211 immediately caused concern owing to the number of alterations in the spike glycoprotein that could lead to antibody evasion. We2 and others3-6 recently reported results confirming such a concern. Continuing surveillance of the evolution of Omicron has since revealed the rise in prevalence of two sublineages, BA.1 with an R346K alteration (BA.1+R346K, also known as BA.1.1) and B.1.1.529.2 (BA.2), with the latter containing 8 unique spike alterations and lacking 13 spike alterations found in BA.1. Here we extended our studies to include antigenic characterization of these new sublineages. Polyclonal sera from patients infected by wild-type SARS-CoV-2 or recipients of current mRNA vaccines showed a substantial loss in neutralizing activity against both BA.1+R346K and BA.2, with drops comparable to that already reported for BA.1 (refs. 2,3,5,6). These findings indicate that these three sublineages of Omicron are antigenically equidistant from the wild-type SARS-CoV-2 and thus similarly threaten the efficacies of current vaccines. BA.2 also exhibited marked resistance to 17 of 19 neutralizing monoclonal antibodies tested, including S309 (sotrovimab)7, which had retained appreciable activity against BA.1 and BA.1+R346K (refs. 2-4,6). This finding shows that no authorized monoclonal antibody therapy could adequately cover all sublineages of the Omicron variant, except for the recently authorized LY-CoV1404 (bebtelovimab).

Fast and efficient template-mediated synthesis of genetic variants.

Efficient methods for the generation of specific mutations enable the study of functional variations in natural populations and lead to advances in genetic engineering applications. Here, we present a new approach, mutagenesis by template-guided amplicon assembly (MEGAA), for the rapid construction of kilobase-sized DNA variants. With this method, many mutations can be generated at a time to a DNA template at more than 90% efficiency per target in a predictable manner. We devised a robust and iterative protocol for an open-source laboratory automation robot that enables desktop production and long-read sequencing validation of variants. Using this system, we demonstrated the construction of 31 natural SARS-CoV2 spike gene variants and 10 recoded Escherichia coli genome fragments, with each 4 kb region containing up to 150 mutations. Furthermore, 125 defined combinatorial adeno-associated virus-2 cap gene variants were easily built using the system, which exhibited viral packaging enhancements of up to 10-fold compared with wild type. Thus, the MEGAA platform enables generation of multi-site sequence variants quickly, cheaply, and in a scalable manner for diverse applications in biotechnology.

DNA-based memory devices for recording cellular events.

Measuring biological data across time and space is critical for understanding complex biological processes and for various biosurveillance applications. However, such data are often inaccessible or difficult to directly obtain. Less invasive, more robust and higher-throughput biological recording tools are needed to profile cells and their environments. DNA-based cellular recording is an emerging and powerful framework for tracking intracellular and extracellular biological events over time across living cells and populations. Here, we review and assess DNA recorders that utilize CRISPR nucleases, integrases and base-editing strategies, as well as recombinase and polymerase-based methods. Quantitative characterization, modelling and evaluation of these DNA-recording modalities can guide their design and implementation for specific application areas.

Engineering living and regenerative fungal-bacterial biocomposite structures.

Engineered living materials could have the capacity to self-repair and self-replicate, sense local and distant disturbances in their environment, and respond with functionalities for reporting, actuation or remediation. However, few engineered living materials are capable of both responsivity and use in macroscopic structures. Here we describe the development, characterization and engineering of a fungal-bacterial biocomposite grown on lignocellulosic feedstocks that can form mouldable, foldable and regenerative living structures. We have developed strategies to make human-scale biocomposite structures using mould-based and origami-inspired growth and assembly paradigms. Microbiome profiling of the biocomposite over multiple generations enabled the identification of a dominant bacterial component, Pantoea agglomerans, which was further isolated and developed into a new chassis. We introduced engineered P. agglomerans into native feedstocks to yield living blocks with new biosynthetic and sensing-reporting capabilities. Bioprospecting the native microbiota to develop engineerable chassis constitutes an important strategy to facilitate the development of living biomaterials with new properties and functionalities.

Robust direct digital-to-biological data storage in living cells.

DNA has been the predominant information storage medium for biology and holds great promise as a next-generation high-density data medium in the digital era. Currently, the vast majority of DNA-based data storage approaches rely on in vitro DNA synthesis. As such, there are limited methods to encode digital data into the chromosomes of living cells in a single step. Here, we describe a new electrogenetic framework for direct storage of digital data in living cells. Using an engineered redox-responsive CRISPR adaptation system, we encoded binary data in 3-bit units into CRISPR arrays of bacterial cells by electrical stimulation. We demonstrate multiplex data encoding into barcoded cell populations to yield meaningful information storage and capacity up to 72 bits, which can be maintained over many generations in natural open environments. This work establishes a direct digital-to-biological data storage framework and advances our capacity for information exchange between silicon- and carbon-based entities.

Metagenomic engineering of the mammalian gut microbiome in situ.

Engineering of microbial communities in open environments remains challenging. Here we describe a platform used to identify and modify genetically tractable mammalian microbiota by engineering community-wide horizontal gene transfer events in situ. With this approach, we demonstrate that diverse taxa in the mouse gut microbiome can be modified directly with a desired genetic payload. In situ microbiome engineering in living animals allows novel capabilities to be introduced into established communities in their native milieu.

Quantifying spatiotemporal variability and noise in absolute microbiota abundances using replicate sampling.

Metagenomic sequencing has enabled detailed investigation of diverse microbial communities, but understanding their spatiotemporal variability remains an important challenge. Here, we present decomposition of variance using replicate sampling (DIVERS), a method based on replicate sampling and spike-in sequencing. The method quantifies the contributions of temporal dynamics, spatial sampling variability, and technical noise to the variances and covariances of absolute bacterial abundances. We applied DIVERS to investigate a high-resolution time series of the human gut microbiome and a spatial survey of a soil bacterial community in Manhattan's Central Park. Our analysis showed that in the gut, technical noise dominated the abundance variability for nearly half of the detected taxa. DIVERS also revealed substantial spatial heterogeneity of gut microbiota, and high temporal covariances of taxa within the Bacteroidetes phylum. In the soil community, spatial variability primarily contributed to abundance fluctuations at short time scales (weeks), while temporal variability dominated at longer time scales (several months).

Scalable and cost-effective ribonuclease-based rRNA depletion for transcriptomics.

Bacterial RNA sequencing (RNA-seq) is a powerful approach for quantitatively delineating the global transcriptional profiles of microbes in order to gain deeper understanding of their physiology and function. Cost-effective bacterial RNA-seq requires efficient physical removal of ribosomal RNA (rRNA), which otherwise dominates transcriptomic reads. However, current methods to effectively deplete rRNA of diverse non-model bacterial species are lacking. Here, we describe a probe and ribonuclease based strategy for bacterial rRNA removal. We implemented the method using either chemically synthesized oligonucleotides or amplicon-based single-stranded DNA probes and validated the technique on three novel gut microbiota isolates from three distinct phyla. We further showed that different probe sets can be used on closely related species. We provide a detailed methods protocol, probe sets for >5000 common microbes from RefSeq, and an online tool to generate custom probe libraries. This approach lays the groundwork for large-scale and cost-effective bacterial transcriptomics studies.

Metagenomic mining of regulatory elements enables programmable species-selective gene expression.

Robust and predictably performing synthetic circuits rely on the use of well-characterized regulatory parts across different genetic backgrounds and environmental contexts. Here we report the large-scale metagenomic mining of thousands of natural 5' regulatory sequences from diverse bacteria, and their multiplexed gene expression characterization in industrially relevant microbes. We identified sequences with broad and host-specific expression properties that are robust in various growth conditions. We also observed substantial differences between species in terms of their capacity to utilize exogenous regulatory sequences. Finally, we demonstrate programmable species-selective gene expression that produces distinct and diverse output patterns in different microbes. Together, these findings provide a rich resource of characterized natural regulatory sequences and a framework that can be used to engineer synthetic gene circuits with unique and tunable cross-species functionality and properties, and also suggest the prospect of ultimately engineering complex behaviors at the community level.

Programmable CRISPR-Cas transcriptional activation in bacteria.

Programmable gene activation enables fine-tuned regulation of endogenous and synthetic gene circuits to control cellular behavior. While CRISPR-Cas-mediated gene activation has been extensively developed for eukaryotic systems, similar strategies have been difficult to implement in bacteria. Here, we present a generalizable platform for screening and selection of functional bacterial CRISPR-Cas transcription activators. Using this platform, we identified a novel CRISPR activator, dCas9-AsiA, that could activate gene expression by more than 200-fold across genomic and plasmid targets with diverse promoters after directed evolution. The evolved dCas9-AsiA can simultaneously mediate activation and repression of bacterial regulons in E. coli. We further identified hundreds of promoters with varying basal expression that could be induced by dCas9-AsiA, which provides a rich resource of genetic parts for inducible gene activation. Finally, we show that dCas9-AsiA can be ported to other bacteria of clinical and bioindustrial relevance, thus enabling bacterial CRISPRa in more application areas. This work expands the toolbox for programmable gene regulation in bacteria and provides a useful resource for future engineering of other bacterial CRISPR-based gene regulators.

Characterizing posttranslational modifications in prokaryotic metabolism using a multiscale workflow.

Understanding the complex interactions of protein posttranslational modifications (PTMs) represents a major challenge in metabolic engineering, synthetic biology, and the biomedical sciences. Here, we present a workflow that integrates multiplex automated genome editing (MAGE), genome-scale metabolic modeling, and atomistic molecular dynamics to study the effects of PTMs on metabolic enzymes and microbial fitness. This workflow incorporates complementary approaches across scientific disciplines; provides molecular insight into how PTMs influence cellular fitness during nutrient shifts; and demonstrates how mechanistic details of PTMs can be explored at different biological scales. As a proof of concept, we present a global analysis of PTMs on enzymes in the metabolic network of Escherichia coli Based on our workflow results, we conduct a more detailed, mechanistic analysis of the PTMs in three proteins: enolase, serine hydroxymethyltransferase, and transaldolase. Application of this workflow identified the roles of specific PTMs in observed experimental phenomena and demonstrated how individual PTMs regulate enzymes, pathways, and, ultimately, cell phenotypes.

Multiplex transcriptional characterizations across diverse bacterial species using cell-free systems.

Cell-free expression systems enable rapid prototyping of genetic programs in vitro. However, current throughput of cell-free measurements is limited by the use of channel-limited fluorescent readouts. Here, we describe DNA Regulatory element Analysis by cell-Free Transcription and Sequencing (DRAFTS), a rapid and robust in vitro approach for multiplexed measurement of transcriptional activities from thousands of regulatory sequences in a single reaction. We employ this method in active cell lysates developed from ten diverse bacterial species. Interspecies analysis of transcriptional profiles from > 1,000 diverse regulatory sequences reveals functional differences in promoter activity that can be quantitatively modeled, providing a rich resource for tuning gene expression in diverse bacterial species. Finally, we examine the transcriptional capacities of dual-species hybrid lysates that can simultaneously harness gene expression properties of multiple organisms. We expect that this cell-free multiplex transcriptional measurement approach will improve genetic part prototyping in new bacterial chassis for synthetic biology.

The effect of short-course antibiotics on the resistance profile of colonizing gut bacteria in the ICU: a prospective cohort study.

BACKGROUND: The need for early antibiotics in the intensive care unit (ICU) is often balanced against the goal of antibiotic stewardship. Long-course antibiotics increase the burden of antimicrobial resistance within colonizing gut bacteria, but the dynamics of this process are not fully understood. We sought to determine how short-course antibiotics affect the antimicrobial resistance phenotype and genotype of colonizing gut bacteria in the ICU by performing a prospective cohort study with assessments of resistance at ICU admission and exactly 72 h later. METHODS: Deep rectal swabs were performed on 48 adults at the time of ICU admission and exactly 72 h later, including patients who did and did not receive antibiotics. To determine resistance phenotype, rectal swabs were cultured for methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus (VRE). In addition, Gram-negative bacterial isolates were cultured against relevant antibiotics. To determine resistance genotype, quantitative PCR (qPCR) was performed from rectal swabs for 87 established resistance genes. Within-individual changes in antimicrobial resistance were calculated based on culture and qPCR results and correlated with exposure to relevant antibiotics (e.g., did ß-lactam antibiotic exposure associate with a detectable change in ß-lactam resistance over this 72-h period?). RESULTS: Of 48 ICU patients, 41 (85%) received antibiotics. Overall, there was no increase in the antimicrobial resistance profile of colonizing gut bacteria during the 72-h study period. There was also no increase in antimicrobial resistance after stratification by receipt of antibiotics (i.e., no detectable increase in ß-lactam, vancomycin, or macrolide resistance regardless of whether patients received those same antibiotics). This was true for both culture and PCR. Antimicrobial resistance pattern at ICU admission strongly predicted resistance pattern after 72 h. CONCLUSIONS: Short-course ICU antibiotics made little detectable difference in the antimicrobial resistance pattern of colonizing gut bacteria over 72 h in the ICU. This provides an improved understanding of the dynamics of antimicrobial resistance in the ICU and some reassurance that short-course antibiotics may not adversely impact the stewardship goal of reducing antimicrobial resistance.

Manipulating Bacterial Communities by in situ Microbiome Engineering.

Microbial communities inhabit our entire planet and have a crucial role in biogeochemical processes, agriculture, biotechnology, and human health. Here, we argue that 'in situ microbiome engineering' represents a new paradigm of community-scale genetic and microbial engineering. We discuss contemporary applications of this approach to directly add, remove, or modify specific sets of functions and alter community-level properties in terrestrial, aquatic, and host-associated microbial communities. Specifically, we highlight emerging in situ genome engineering approaches as tractable techniques to manipulate microbial communities with high specificity and efficacy. Finally, we describe opportunities for technological innovation and ways to bridge existing knowledge gaps to accelerate the development of in situ approaches for microbiome manipulations.

The Role of Genome Accessibility in Transcription Factor Binding in Bacteria.

ChIP-seq enables genome-scale identification of regulatory regions that govern gene expression. However, the biological insights generated from ChIP-seq analysis have been limited to predictions of binding sites and cooperative interactions. Furthermore, ChIP-seq data often poorly correlate with in vitro measurements or predicted motifs, highlighting that binding affinity alone is insufficient to explain transcription factor (TF)-binding in vivo. One possibility is that binding sites are not equally accessible across the genome. A more comprehensive biophysical representation of TF-binding is required to improve our ability to understand, predict, and alter gene expression. Here, we show that genome accessibility is a key parameter that impacts TF-binding in bacteria. We developed a thermodynamic model that parameterizes ChIP-seq coverage in terms of genome accessibility and binding affinity. The role of genome accessibility is validated using a large-scale ChIP-seq dataset of the M. tuberculosis regulatory network. We find that accounting for genome accessibility led to a model that explains 63% of the ChIP-seq profile variance, while a model based in motif score alone explains only 35% of the variance. Moreover, our framework enables de novo ChIP-seq peak prediction and is useful for inferring TF-binding peaks in new experimental conditions by reducing the need for additional experiments. We observe that the genome is more accessible in intergenic regions, and that increased accessibility is positively correlated with gene expression and anti-correlated with distance to the origin of replication. Our biophysically motivated model provides a more comprehensive description of TF-binding in vivo from first principles towards a better representation of gene regulation in silico, with promising applications in systems biology.