Beyond Normalization: Incorporating Scale Uncertainty in Microbiome and Gene Expression Analysis.

Though statistical normalizations are often used in differential abundance or differential expression analysis to address sample-to-sample variation in sequencing depth, we offer a better alternative. These normalizations often make strong, implicit assumptions about the scale of biological systems (e.g., microbial load). Thus, analyses are susceptible to even slight errors in these assumptions, leading to elevated rates of false positives and false negatives. We introduce scale models as a generalization of normalizations so researchers can model potential errors in assumptions about scale. By incorporating scale models into the popular ALDEx2 software, we enhance the reproducibility of analyses while often drastically decreasing false positive and false negative rates. We design scale models that are guaranteed to reduce false positives compared to equivalent normalizations. At least in the context of ALDEx2, we recommend using scale models over normalizations in all practical situations.

De Novo Synthesis of a Conjugative System from Human Gut Metagenomic Data for Targeted Delivery of Cas9 Antimicrobials.

Metagenomic sequences represent an untapped source of genetic novelty, particularly for conjugative systems that could be used for plasmid-based delivery of Cas9-derived antimicrobial agents. However, unlocking the functional potential of conjugative systems purely from metagenomic sequences requires the identification of suitable candidate systems as starting scaffolds for de novo DNA synthesis. Here, we developed a bioinformatics approach that searches through the metagenomic "trash bin" for genes associated with conjugative systems present on contigs that are typically excluded from common metagenomic analysis pipelines. Using a human metagenomic gut data set representing 2805 taxonomically distinct units, we identified 1598 contigs containing conjugation genes with a differential distribution in human cohorts. We synthesized de novo an entire Citrobacter spp. conjugative system of 54 kb containing at least 47 genes and assembled it into a plasmid, pCitro. We found that pCitro conjugates from Escherichia coli to Citrobacter rodentium with a 30-fold higher frequency than to E. coli, and is compatible with Citrobacter resident plasmids. Mutations in the traV and traY conjugation components of pCitro inhibited conjugation. We showed that pCitro can be repurposed as an antimicrobial delivery agent by programming it with the TevCas9 nuclease and Citrobacter-specific sgRNAs to kill C. rodentium. Our study reveals a trove of uncharacterized conjugative systems in metagenomic data and describes an experimental framework to animate these large genetic systems as novel target-adapted delivery vectors for Cas9-based editing of bacterial genomes.

Multi-site microbiota alteration is a hallmark of kidney stone formation.

BACKGROUND: Inquiry of microbiota involvement in kidney stone disease (KSD) has largely focussed on potential oxalate handling abilities by gut bacteria and the increased association with antibiotic exposure. By systematically comparing the gut, urinary, and oral microbiota of 83 stone formers (SF) and 30 healthy controls (HC), we provide a unified assessment of the bacterial contribution to KSD. RESULTS: Amplicon and shotgun metagenomic sequencing approaches were consistent in identifying multi-site microbiota disturbances in SF relative to HC. Biomarker taxa, reduced taxonomic and functional diversity, functional replacement of core bioenergetic pathways with virulence-associated gene markers, and community network collapse defined SF, but differences between cohorts did not extend to oxalate metabolism. CONCLUSIONS: We conclude that multi-site microbiota alteration is a hallmark of SF, and KSD treatment should consider microbial functional restoration and the avoidance of aberrant modulators such as poor diet and antibiotics where applicable to prevent stone recurrence. Video Abstract.

A generalizable Cas9/sgRNA prediction model using machine transfer learning with small high-quality datasets.

The CRISPR/Cas9 nuclease from Streptococcus pyogenes (SpCas9) can be used with single guide RNAs (sgRNAs) as a sequence-specific antimicrobial agent and as a genome-engineering tool. However, current bacterial sgRNA activity models struggle with accurate predictions and do not generalize well, possibly because the underlying datasets used to train the models do not accurately measure SpCas9/sgRNA activity and cannot distinguish on-target cleavage from toxicity. Here, we solve this problem by using a two-plasmid positive selection system to generate high-quality data that more accurately reports on SpCas9/sgRNA cleavage and that separates activity from toxicity. We develop a machine learning architecture (crisprHAL) that can be trained on existing datasets, that shows marked improvements in sgRNA activity prediction accuracy when transfer learning is used with small amounts of high-quality data, and that can generalize predictions to different bacteria. The crisprHAL model recapitulates known SpCas9/sgRNA-target DNA interactions and provides a pathway to a generalizable sgRNA bacterial activity prediction tool that will enable accurate antimicrobial and genome engineering applications.

Metabolically-targeted dCas9 expression in bacteria.

The ability to restrict gene expression to a relevant bacterial species in a complex microbiome is an unsolved problem. In the context of the human microbiome, one desirable target metabolic activity are glucuronide-utilization enzymes (GUS) that are implicated in the toxic re-activation of glucuronidated compounds in the human gastrointestinal (GI) tract, including the chemotherapeutic drug irinotecan. Here, we take advantage of the variable distribution of GUS enzymes in bacteria as a means to distinguish between bacteria with GUS activity, and re-purpose the glucuronide-responsive GusR transcription factor as a biosensor to regulate dCas9 expression in response to glucuronide inducers. We fused the Escherichia coli gusA regulatory region to the dCas9 gene to create pGreg-dCas9, and showed that dCas9 expression is induced by glucuronides, but not other carbon sources. When conjugated from E. coli to Gammaproteobacteria derived from human stool, dCas9 expression from pGreg-dCas9 was restricted to GUS-positive bacteria. dCas9-sgRNAs targeted to gusA specifically down-regulated gus operon transcription in Gammaproteobacteria, with a resulting ∼100-fold decrease in GusA activity. Our data outline a general strategy to re-purpose bacterial transcription factors responsive to exogenous metabolites for precise ligand-dependent expression of genetic tools such as dCas9 in diverse bacterial species.

Telomere-to-telomere genome assembly of Phaeodactylum tricornutum.

Phaeodactylum tricornutum is a marine diatom with a growing genetic toolbox available and is being used in many synthetic biology applications. While most of the genome has been assembled, the currently available genome assembly is not a completed telomere-to-telomere assembly. Here, we used Oxford Nanopore long reads to build a telomere-to-telomere genome for Phaeodactylum tricornutum. We developed a graph-based approach to extract all unique telomeres, and used this information to manually correct assembly errors. In total, we found 25 nuclear chromosomes that comprise all previously assembled fragments, in addition to the chloroplast and mitochondrial genomes. We found that chromosome 19 has filtered long-read coverage and a quality estimate that suggests significantly less haplotype sequence variation than the other chromosomes. This work improves upon the previous genome assembly and provides new opportunities for genetic engineering of this species, including creating designer synthetic chromosomes.

Phosphate-regulated expression of the SARS-CoV-2 receptor-binding domain in the diatom Phaeodactylum tricornutum for pandemic diagnostics.

The worldwide COVID-19 pandemic caused by the SARS-CoV-2 betacoronavirus has highlighted the need for a synthetic biology approach to create reliable and scalable sources of viral antigen for uses in diagnostics, therapeutics and basic biomedical research. Here, we adapt plasmid-based systems in the eukaryotic microalgae Phaeodactylum tricornutum to develop an inducible overexpression system for SARS-CoV-2 proteins. Limiting phosphate and iron in growth media induced expression of the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein from the P. tricornutum HASP1 promoter in the wild-type strain and in a histidine auxotrophic strain that alleviates the requirement for antibiotic selection of expression plasmids. The RBD was purified from whole cell extracts (algae-RBD) with yield compromised by the finding that 90-95% of expressed RBD lacked the genetically encoded C-terminal 6X-histidine tag. Constructs that lacked the TEV protease site between the RBD and C-terminal 6X-histidine tag retained the tag, increasing yield. Purified algae-RBD was found to be N-linked glycosylated by treatment with endoglycosidases, was cross-reactive with anti-RBD polyclonal antibodies, and inhibited binding of recombinant RBD purified from mammalian cell lines to the human ACE2 receptor. We also show that the algae-RBD can be used in a lateral flow assay device to detect SARS-CoV-2 specific IgG antibodies from donor serum at sensitivity equivalent to assays performed with RBD made in mammalian cell lines. Our study shows that P. tricornutum is a scalable system with minimal biocontainment requirements for the inducible production of SARS-CoV-2 or other coronavirus antigens for pandemic diagnostics.

Superior Conjugative Plasmids Delivered by Bacteria to Diverse Fungi.

Fungi are nature's recyclers, allowing for ecological nutrient cycling and, in turn, the continuation of life on Earth. Some fungi inhabit the human microbiome where they can provide health benefits, while others are opportunistic pathogens that can cause disease. Yeasts, members of the fungal kingdom, have been domesticated by humans for the production of beer, bread, and, recently, medicine and chemicals. Still, the great untapped potential exists within the diverse fungal kingdom. However, many yeasts are intractable, preventing their use in biotechnology or in the development of novel treatments for pathogenic fungi. Therefore, as a first step for the domestication of new fungi, an efficient DNA delivery method needs to be developed. Here, we report the creation of superior conjugative plasmids and demonstrate their transfer via conjugation from bacteria to 7 diverse yeast species including the emerging pathogen Candida auris. To create our superior plasmids, derivatives of the 57 kb conjugative plasmid pTA-Mob 2.0 were built using designed gene deletions and insertions, as well as some unintentional mutations. Specifically, a cluster mutation in the promoter of the conjugative gene traJ had the most significant effect on improving conjugation to yeasts. In addition, we created Golden Gate assembly-compatible plasmid derivatives that allow for the generation of custom plasmids to enable the rapid insertion of designer genetic cassettes. Finally, we demonstrated that designer conjugative plasmids harboring engineered restriction endonucleases can be used as a novel antifungal agent, with important applications for the development of next-generation antifungal therapeutics.

Preen gland microbiota of songbirds differ across populations but not sexes.

Metabolites produced by symbiotic microbes can affect the odour of their hosts, providing olfactory cues of identity, sex or other salient features. In birds, preen oil is a major source of body odour that differs between populations and sexes. We hypothesized that population and sex differences in preen oil chemistry reflect underlying differences in preen gland microbiota, predicting that these microbes also differ among populations and between the sexes. We further predicted that pairwise similarity in the community composition of preen gland microbiota would covary with that of preen oil chemical composition, consistent with the fermentation hypothesis for chemical recognition. We analysed preen oil chemistry and preen gland bacterial communities of song sparrows Melospiza melodia. Birds were sampled at sites for which population and sex differences in preen oil have been reported, and at a third site that has been less studied. Consistent with prior work in this system, we found population and sex differences in preen oil chemistry. By contrast, we found population differences but not sex differences in the community composition of preen gland microbes. Overall similarity in the community composition of preen gland microbiota did not significantly covary with that of preen oil chemistry. However, we identified a subset of six microbial genera that maximally correlated with preen oil composition. Although both preen gland microbiota and preen oil composition differ across populations, we did not observe an overall association between them that would implicate symbiotic microbes in mediating variation in olfactory cues associated with preen oil. Instead, certain subsets of microbes may be involved in mediating olfactory cues in birds, but experiments are required to test this.

Pannexin 1 mutation found in melanoma tumor reduces phosphorylation, glycosylation, and trafficking of the channel-forming protein.

Pannexin 1 (PANX1) is a glycoprotein that forms large pore channels capable of passing ions and metabolites such as ATP for cellular communication. PANX1 has been implicated in many diseases including breast cancer and melanoma, where inhibition or deletion of PANX1 reduced the tumorigenic and metastatic properties of the cancer cells. We interrogated the effect of single amino acid changes in various PANX1 domains using naturally occurring variants reported in cancer patient tumors. We found that a previously reported variant (Q5H) is present in cancer cells, but was not different from the wild type (Q5) in glycosylation, trafficking, or channel function and did not affect cellular properties. We discovered that the Q5H variant is in fact the highly conserved ancestral allele of PANX1 with 89% of humans carrying at least one Q5H allele. Another mutated form Y150F, found in a melanoma patient tumor, prevented phosphorylation at Y150 as well as complex N-glycosylation while increasing intracellular localization. Sarcoma (SRC) is the predicted kinase to phosphorylate the Y150 residue, and its phosphorylation is not likely to be constitutive, but rather dynamically regulated. The Y150 phosphorylation site is the first one reported to play a role in regulating posttranslational modifications and trafficking of PANX1, with potential consequences on its large-pore channel structure and function in melanoma cells.

Ureteral Stent Microbiota Is Associated with Patient Comorbidities but Not Antibiotic Exposure.

Ureteral stents are commonly used to prevent urinary obstruction but can become colonized by bacteria and encrusted, leading to clinical complications. Despite recent discovery and characterization of the healthy urinary microbiota, stent-associated bacteria and their impact on encrustation are largely underexplored. We profile the microbiota of patients with typical short-term stents, as well as over 30 atypical cases (all with paired mid-stream urine) from 241 patients. Indwelling time, age, and various patient comorbidities correlate with alterations to the stent microbiota composition, whereas antibiotic exposure, urinary tract infection (UTI), and stent placement method do not. The stent microbiota most likely originates from adhesion of resident urinary microbes but subsequently diverges to a distinct, reproducible population, thereby negating the urine as a biomarker for stent encrustation or microbiota. Urological practice should reconsider standalone prophylactic antibiotics in favor of tailored therapies based on patient comorbidities in efforts to minimize bacterial burden, encrustation, and complications of ureteral stents.

Cloning of Thalassiosira pseudonana's Mitochondrial Genome in Saccharomyces cerevisiae and Escherichia coli.

Algae are attractive organisms for biotechnology applications such as the production of biofuels, medicines, and other high-value compounds due to their genetic diversity, varied physical characteristics, and metabolic processes. As new species are being domesticated, rapid nuclear and organelle genome engineering methods need to be developed or optimized. To that end, we have previously demonstrated that the mitochondrial genome of microalgae Phaeodactylum tricornutum can be cloned and engineered in Saccharomyces cerevisiae and Escherichia coli. Here, we show that the same approach can be used to clone mitochondrial genomes of another microalga, Thalassiosira pseudonana. We have demonstrated that these genomes can be cloned in S. cerevisiae as easily as those of P. tricornutum, but they are less stable when propagated in E. coli. Specifically, after approximately 60 generations of propagation in E. coli, 17% of cloned T. pseudonana mitochondrial genomes contained deletions compared to 0% of previously cloned P. tricornutum mitochondrial genomes. This genome instability is potentially due to the lower G+C DNA content of T. pseudonana (30%) compared to P. tricornutum (35%). Consequently, the previously established method can be applied to clone T. pseudonana's mitochondrial genome, however, more frequent analyses of genome integrity will be required following propagation in E. coli prior to use in downstream applications.

Effect of Oral Probiotic Lactobacillus rhamnosus GR-1 and Lactobacillus reuteri RC-14 on the Vaginal Microbiota, Cytokines and Chemokines in Pregnant Women.

Spontaneous preterm birth is associated with vaginal microbial dysbiosis. As certain strains of lactobacilli help restore homeostasis in non-pregnant women, the goal was to determine the effect of Lactobacillus rhamnosus GR-1 and Lactobacillus reuteri RC-14 administered orally, twice daily for 12 weeks on the vaginal microbiota, cytokines and chemokines of low-risk pregnant women. A double-blind, placebo-controlled, randomized trial comparing probiotic lactobacilli to placebo daily was performed in 86 asymptomatic pregnant women who had an Intermediate or Bacterial Vaginosis Nugent score at 13 weeks. After drop outs, 32 women receiving probiotics and 34 receiving placebo completed the study. The Nugent score returned to normal in 30% of the women in both groups at 28 weeks and was maintained until 35 weeks. The majority of subjects had normal pregnancy outcomes. Ninety-three bacterial species were detected at 13 weeks, with Lactobacillus iners, Lactobacillus crispatus, Gardnerella vaginalis and Atopobium vaginae being the most abundant across pregnancy. There was no difference in the Shannon diversity index between the probiotic and placebo groups at 13, 28 or 35 weeks. Almost all subjects consumed fermented foods and many of the organisms in the vagina are also known to be present in fermented foods. Interleukin-4 in the placebo group and Interleukin-10 in both probiotic and placebo groups increased slightly at 28 weeks but were not different at 35 weeks when compared to 13 weeks. In conclusion, this study showed no adverse issues resulting from 12 week use of probiotic Lactobacillus strains GR-1 and RC-14 during pregnancy in women at low risk for premature birth. The vaginal microbiota demonstrated flux irrespective of this oral probiotic administration.

omicplotR: visualizing omic datasets as compositions.

BACKGROUND: Differential abundance analysis is widely used with high-throughput sequencing data to compare gene abundance or expression between groups of samples. Many software packages exist for this purpose, but each uses a unique set of statistical assumptions to solve problems on a case-by-case basis. These software packages are typically difficult to use for researchers without command-line skills, and software that does offer a graphical user interface do not use a compositionally valid method. RESULTS: omicplotR facilitates visual exploration of omic datasets for researchers with and without prior scripting knowledge. Reproducible visualizations include principal component analysis, hierarchical clustering, MA plots and effect plots. We demonstrate the functionality of omicplotR using a publicly available metatranscriptome dataset. CONCLUSIONS: omicplotR provides a graphical user interface to explore sequence count data using generalizable compositional methods, facilitating visualization for investigators without command-line experience.

Efficient inter-species conjugative transfer of a CRISPR nuclease for targeted bacterial killing.

The selective regulation of bacteria in complex microbial populations is key to controlling pathogenic bacteria. CRISPR nucleases can be programmed to kill bacteria, but require an efficient and broad-host range delivery system to be effective. Here, using an Escherichia coli and Salmonella enterica co-culture system, we show that plasmids based on the IncP RK2 conjugative system can be used as delivery vectors for a TevSpCas9 dual nuclease. Notably, a cis-acting plasmid that encodes the conjugation and CRISPR machinery conjugates from E. coli to S. enterica with high frequency compared to a trans system that separates conjugation and CRISPR machinery. In culture conditions that enhance cell-to-cell contact, conjugation rates approach 100% with the cis-acting plasmid. Targeting of single or multiplexed sgRNAs to non-essential genes results in high S. enterica killing efficiencies. Our data highlight the potential of cis-acting conjugative plasmids as a delivery system for CRISPR nucleases or other microbial-altering agents for targeted bacterial killing.

Modifying a covarying protein-DNA interaction changes substrate preference of a site-specific endonuclease.

Identifying and validating intermolecular covariation between proteins and their DNA-binding sites can provide insights into mechanisms that regulate selectivity and starting points for engineering new specificity. LAGLIDADG homing endonucleases (meganucleases) can be engineered to bind non-native target sites for gene-editing applications, but not all redesigns successfully reprogram specificity. To gain a global overview of residues that influence meganuclease specificity, we used information theory to identify protein-DNA covariation. Directed evolution experiments of one predicted pair, 227/+3, revealed variants with surprising shifts in I-OnuI substrate preference at the central 4 bases where cleavage occurs. Structural studies showed significant remodeling distant from the covarying position, including restructuring of an inter-hairpin loop, DNA distortions near the scissile phosphates, and new base-specific contacts. Our findings are consistent with a model whereby the functional impacts of covariation can be indirectly propagated to neighboring residues outside of direct contact range, allowing meganucleases to adapt to target site variation and indirectly expand the sequence space accessible for cleavage. We suggest that some engineered meganucleases may have unexpected cleavage profiles that were not rationally incorporated during the design process.

Targeted sequencing reveals expanded genetic diversity of human transfer RNAs.

Transfer RNAs are required to translate genetic information into proteins as well as regulate other cellular processes. Nucleotide changes in tRNAs can result in loss or gain of function that impact the composition and fidelity of the proteome. Despite links between tRNA variation and disease, the importance of cytoplasmic tRNA variation has been overlooked. Using a custom capture panel, we sequenced 605 human tRNA-encoding genes from 84 individuals. We developed a bioinformatic pipeline that allows more accurate tRNA read mapping and identifies multiple polymorphisms occurring within the same variant. Our analysis identified 522 unique tRNA-encoding sequences that differed from the reference genome from 84 individuals. Each individual had ~66 tRNA variants including nine variants found in less than 5% of our sample group. Variants were identified throughout the tRNA structure with 17% predicted to enhance function. Eighteen anticodon mutants were identified including potentially mistranslating tRNAs; e.g., a tRNASer that decodes Phe codons. Similar engineered tRNA variants were previously shown to inhibit cell growth, increase apoptosis and induce the unfolded protein response in mammalian cell cultures and chick embryos. Our analysis shows that human tRNA variation has been underestimated. We conclude that the large number of tRNA genes provides a buffer enabling the emergence of variants, some of which could contribute to disease.

Placental microRNAs in pregnancies with early onset intrauterine growth restriction and preeclampsia: potential impact on gene expression and pathophysiology.

BACKGROUND: A normally developed placenta is integral to a successful pregnancy. Preeclampsia (PE) and intrauterine growth restriction (IUGR) are two common pregnancy related complications that maybe a result of abnormal placental development. Placental microRNAs (miRNAs) have been investigated as potential biomarkers for these complications, as they may play a role in placental development and pathophysiology by influencing gene expression. The purpose of this study is to utilize next-generation sequencing to determine miRNA and gene expression in human placental (chorionic villous) samples from three distinct patient groups with early-onset (EO) PE, IUGR, or PE + IUGR. METHODS: Placental tissues were collected from four patient groups (control [N = 21], EO-PE [N = 20], EO-IUGR [N = 18], and EO-PE + IUGR [N = 20]), and total RNA was used for miRNA and RNA sequencing on the Illumina Hiseq2000 platform. For stringent differential expression analysis multiple analysis programs were used to analyze both expression datasets in each patient group compared to gestational age-matched controls. RESULTS: Analysis revealed miRNAs and genes that are disease-specific, as well as others that were common between disease groups, which suggests common underlying placental pathologies in EO-PE and EO-IUGR. More specifically, 6 miRNAs and 22 genes were identified to be differentially expressed in all three patient groups. In addition, integrative analysis between the miRNA and gene expression datasets revealed candidate gene targets for miRNAs of interest. CONCLUSIONS: Integration of miRNA and RNA profiling in the same three subgroups of pregnancy complications, provides an alternate level of molecular information, in addition it can be used to better understand both unique and common molecular mechanisms involved in the pathophysiology of these diseases.

A Haemophilus sp. dominates the microbiota of sputum from UK adults with non-severe community acquired pneumonia and chronic lung disease.

The demographics and comorbidities of patients with community acquired pneumonia (CAP) vary enormously but stratified treatment is difficult because aetiological studies have failed to comprehensively identify the pathogens. Our aim was to describe the bacterial microbiota of CAP and relate these to clinical characteristics in order to inform future trials of treatment stratified by co-morbidity. CAP patients were prospectively recruited at two UK hospitals. We used 16S rRNA gene sequencing to identify the dominant bacteria in sputum and compositional data analysis to determine associations with patient characteristics. We analysed sputum samples from 77 patients and found a Streptococcus sp. and a Haemophilus sp. were the most relatively abundant pathogens. The Haemophilus sp. was more likely to be dominant in patients with pre-existing lung disease, and its relative abundance was associated with qPCR levels of Haemophilus influenzae. The most abundant Streptococcus sp. was associated with qPCR levels of Streptococcus pneumoniae but dominance could not be predicted from clinical characteristics. These data suggest chronic lung disease influences the microbiota of sputum in patients with CAP. This finding could inform a trial of stratifying empirical CAP antibiotics to target Haemophilus spp. in addition to Streptococcus spp. in those with chronic lung disease.