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Recent advances in spatial transcriptomics (ST) enable gene expression measurements from a tissue sample while retaining its spatial context. This technology enables unprecedented in situ resolution of the regulatory pathways that underlie the heterogeneity in the tumor and its microenvironment (TME). The direct characterization of cellular co-localization with spatial technologies facilities quantification of the molecular changes resulting from direct cell-cell interaction, as occurs in tumor-immune interactions. We present SpaceMarkers, a novel bioinformatics algorithm to infer molecular changes from cell-cell interaction from latent space analysis of ST data. We apply this approach to infer molecular changes from tumor-immune interactions in Visium spatial transcriptomics data of metastasis, invasive and precursor lesions, and immunotherapy treatment. Further transfer learning in matched scRNA-seq data enabled further quantification of the specific cell types in which SpaceMarkers are enriched. Altogether, SpaceMarkers can identify the location and context-specific molecular interactions within the TME from ST data.

Yersinia enterocolitica is typically considered an extracellular pathogen; however, during the course of an infection, a significant number of bacteria are stably maintained within host cell vacuoles. Little is known about this population and the role it plays during an infection. To address this question and to elucidate the spatially and temporally dynamic gene expression patterns of Y. enterocolitica biovar 1B through the course of an in vitro infection, transcriptome sequencing and differential gene expression analysis of bacteria infecting murine macrophage cells were performed under four distinct conditions. Bacteria were first grown in a nutrient-rich medium at 26°C to establish a baseline of gene expression that is unrelated to infection. The transcriptomes of these bacteria were then compared to bacteria grown in a conditioned cell culture medium at 37°C to identify genes that were differentially expressed in response to the increased temperature and medium but not in response to host cells. Infections were then performed, and the transcriptomes of bacteria found on the extracellular surface and intracellular compartments were analyzed individually. The upregulated genes revealed potential roles for a variety of systems in promoting intracellular virulence, including the Ysa type III secretion system, the Yts2 type II secretion system, and the Tad pilus. It was further determined that mutants of each of these systems had decreased virulence while infecting macrophages. Overall, these results reveal the complete set of genes expressed by Y. enterocolitica in response to infection and provide the groundwork for future virulence studies.

A few studies have highlighted the importance of the respiratory microbiome in modulating the frequency and outcome of viral respiratory infections. However, there are insufficient data on the use of microbial signatures as prognostic biomarkers to predict respiratory disease outcomes. In this study, we aimed to evaluate whether specific bacterial community compositions in the nasopharynx of children at the time of hospitalization are associated with different influenza clinical outcomes. We utilized retrospective nasopharyngeal (NP) samples (n=36) collected at the time of hospital arrival from children who were infected with influenza virus and had been symptomatic for less than 2 days. Based on their clinical course, children were classified into two groups: patients with mild influenza, and patients with severe respiratory or neurological complications. We implemented custom 16S rRNA gene sequencing, metagenomic sequencing and computational analysis workflows to classify the bacteria present in NP specimens at the species level. We found that increased bacterial diversity in the nasopharynx of children was strongly associated with influenza severity. In addition, patients with severe influenza had decreased relative abundance of Staphylococcus aureus and increased abundance of Prevotella (including P. melaninogenica), Streptobacillus, Porphyromonas, Granulicatella (including G. elegans), Veillonella (including V. dispar), Fusobacterium and Haemophilus in their nasopharynx. This pilot study provides proof-of-concept data for the use of microbial signatures as prognostic biomarkers of influenza outcomes. Further large prospective cohort studies are needed to refine and validate the performance of such microbial signatures in clinical settings.

Virulence genes on mobile DNAs such as genomic islands (GIs) and plasmids promote bacterial pathogen emergence. Excision is an early step in GI mobilization, producing a circular GI and a deletion site in the chromosome; circular forms are also known for some bacterial insertion sequences (ISs). The recombinant sequence at the junctions of such circles and deletions can be detected sensitively in high-throughput sequencing data, using new computational methods that enable empirical discovery of mobile DNAs. For the rich mobilome of a hospital Klebsiella pneumoniae strain, circularization junctions (CJs) were detected for six GIs and seven IS types. Our methods revealed differential biology of multiple mobile DNAs, imprecision of integrases and transposases, and differential activity among identical IS copies for IS26, ISKpn18 and ISKpn21. Using the resistance of circular dsDNA molecules to exonuclease, internally calibrated with the native plasmids, showed that not all molecules bearing GI CJs were circular. Transpositions were also detected, revealing replicon preference (ISKpn18 prefers a conjugative IncA/C2 plasmid), local action (IS26), regional preferences, selection (against capsule synthesis) and IS polarity inversion. Efficient discovery and global characterization of numerous mobile elements per experiment improves accounting for the new gene combinations that arise in emerging pathogens.

When analyzing pathogen transcriptomes during the infection of host cells, the signal-to-background (pathogen-to-host) ratio of nucleic acids (NA) in infected samples is very small. Despite the advancements in next-generation sequencing, the minute amount of pathogen NA makes standard RNA-seq library preps inadequate for effective gene-level analysis of the pathogen in cases with low bacterial loads. In order to provide a more complete picture of the pathogen transcriptome during an infection, we developed a novel pathogen enrichment technique, which can enrich for transcripts from any cultivable bacteria or virus, using common, readily available laboratory equipment and reagents. To evenly enrich for pathogen transcripts, we generate biotinylated pathogen-targeted capture probes in an enzymatic process using the entire genome of the pathogen as a template. The capture probes are hybridized to a strand-specific cDNA library generated from an RNA sample. The biotinylated probes are captured on a monomeric avidin resin in a miniature spin column, and enriched pathogen-specific cDNA is eluted following a series of washes. To test this method, we performed an in vitro time-course infection using Klebsiella pneumoniae to infect murine macrophage cells. K. pneumoniae transcript enrichment efficiency was evaluated using RNA-seq. Bacterial transcripts were enriched up to ~400-fold, and allowed the recovery of transcripts from ~2000–3600 genes not observed in untreated control samples. These additional transcripts revealed interesting aspects of K. pneumoniae biology including the expression of putative virulence factors and the expression of several genes responsible for antibiotic resistance even in the absence of drugs.

Multidrug-resistant Enterobacteriaceae are emerging as a serious infectious disease challenge. These strains can accumulate many antibiotic resistance genes though horizontal transfer of genetic elements, those for β-lactamases being of particular concern. Some β-lactamases are active on a broad spectrum of β-lactams including the last-resort carbapenems. The gene for the broad-spectrum and carbapenem-active metallo-β-lactamase NDM-1 is rapidly spreading. We present the complete genome of Klebsiella pneumoniae ATCC BAA-2146, the first U.S. isolate found to encode NDM-1, and describe its repertoire of antibiotic-resistance genes and mutations, including genes for eight β-lactamases and 15 additional antibiotic-resistance enzymes. To elucidate the evolution of this rich repertoire, the mobile elements of the genome were characterized, including four plasmids with varying degrees of conservation and mosaicism and eleven chromosomal genomic islands. One island was identified by a novel phylogenomic approach, that further indicated the cps-lps polysaccharide synthesis locus, where operon translocation and fusion was noted. Unique plasmid segments and mosaic junctions were identified. Plasmid-borne bla CTX-M-15 was transposed recently to the chromosome by ISEcp1. None of the eleven full copies of IS26, the most frequent IS element in the genome, had the expected 8-bp direct repeat of the integration target sequence, suggesting that each copy underwent homologous recombination subsequent to its last transposition event. Comparative analysis likewise indicates IS26 as a frequent recombinational junction between plasmid ancestors, and also indicates a resolvase site. In one novel use of high-throughput sequencing, homologously recombinant subpopulations of the bacterial culture were detected. In a second novel use, circular transposition intermediates were detected for the novel insertion sequence ISKpn21 of the ISNCY family, suggesting that it uses the two-step transposition mechanism of IS3. Robust genome-based phylogeny showed that a unified Klebsiella cluster contains Enterobacter aerogenes and Raoultella, suggesting the latter genus should be abandoned.

Francisella tularensis is a zoonotic intracellular pathogen that is capable of causing potentially fatal human infections. Like all successful bacterial pathogens, F. tularensis rapidly responds to changes in its environment during infection of host cells, and upon encountering different microenvironments within those cells. This ability to appropriately respond to the challenges of infection requires rapid and global shifts in gene expression patterns. In this study, we use a novel pathogen transcript enrichment strategy and whole transcriptome sequencing (RNA-Seq) to perform a detailed characterization of the rapid and global shifts in F. tularensis LVS gene expression during infection of murine macrophages. We performed differential gene expression analysis on all bacterial genes at two key stages of infection: phagosomal escape, and cytosolic replication. By comparing the F. tularensis transcriptome at these two stages of infection to that of the bacteria grown in culture, we were able to identify sets of genes that are differentially expressed over the course of infection. This analysis revealed the temporally dynamic expression of a number of known and putative transcriptional regulators and virulence factors, providing insight into their role during infection. In addition, we identified several F. tularensis genes that are significantly up-regulated during infection but had not been previously identified as virulence factors. These unknown genes may make attractive therapeutic or vaccine targets.

Use of second generation sequencing (SGS) technologies for transcriptional profiling (RNA-Seq) has revolutionized transcriptomics, enabling measurement of RNA abundances with unprecedented specificity and sensitivity and the discovery of novel RNA species. Preparation of RNA-Seq libraries requires conversion of the RNA starting material into cDNA flanked by platform-specific adaptor sequences. Each of the published methods and commercial kits currently available for RNA-Seq library preparation suffers from at least one major drawback, including long processing times, large starting material requirements, uneven coverage, loss of strand information and high cost. We report the development of a new RNA-Seq library preparation technique that produces representative, strand-specific RNA-Seq libraries from small amounts of starting material in a fast, simple and cost-effective manner. Additionally, we have developed a new quantitative PCR-based assay for precisely determining the number of PCR cycles to perform for optimal enrichment of the final library, a key step in all SGS library preparation workflows.

To fully understand the interactions of a pathogen with its host, it is necessary to analyze the RNA transcripts of both the host and pathogen throughout the course of an infection. Although this can be accomplished relatively easily on the host side, the analysis of pathogen transcripts is complicated by the overwhelming amount of host RNA isolated from an infected sample. Even with the read depth provided by second-generation sequencing, it is extremely difficult to get enough pathogen reads for an effective gene-level analysis. In this study, we describe a novel capture-based technique and device that considerably enriches for pathogen transcripts from infected samples. This versatile method can, in principle, enrich for any pathogen in any infected sample. To test the technique's efficacy, we performed time course tissue culture infections using Rift Valley fever virus and Francisella tularensis. At each time point, RNA sequencing (RNA-Seq) was performed and the results of the treated samples were compared with untreated controls. The capture of pathogen transcripts, in all cases, led to more than an order of magnitude enrichment of pathogen reads, greatly increasing the number of genes hit, the coverage of those genes, and the depth at which each transcript was sequenced.

Next-generation sequencing (NGS) is emerging as a powerful tool for elucidating genetic information for a wide range of applications. Unfortunately, the surging popularity of NGS has not yet been accompanied by an improvement in automated techniques for preparing formatted sequencing libraries. To address this challenge, we have developed a prototype microfluidic system for preparing sequencer-ready DNA libraries for analysis by Illumina sequencing. Our system combines droplet-based digital microfluidic (DMF) sample handling with peripheral modules to create a fully-integrated, sample-in library-out platform. In this report, we use our automated system to prepare NGS libraries from samples of human and bacterial genomic DNA. E. coli libraries prepared on-device from 5 ng of total DNA yielded excellent sequence coverage over the entire bacterial genome, with >99% alignment to the reference genome, even genome coverage, and good quality scores. Furthermore, we produced a de novo assembly on a previously unsequenced multi-drug resistant Klebsiella pneumoniae strain BAA-2146 (KpnNDM). The new method described here is fast, robust, scalable, and automated. Our device for library preparation will assist in the integration of NGS technology into a wide variety of laboratories, including small research laboratories and clinical laboratories.

Second-generation sequencing (SGS) has become the preferred method for RNA transcriptome profiling of organisms and single cells. However, SGS analysis of transcriptome diversity (including protein-coding transcripts and regulatory non-coding RNAs) is inefficient unless the sample of interest is first depleted of nucleic acids derived from ribosomal RNA (rRNA), which typically account for up to 95% of total intracellular RNA content. Here we describe a novel microscale hydroxyapatite chromatography (HAC) normalization method to remove eukaryotic and prokaryotic high abundant rRNA species, thereby increasing sequence coverage depth and transcript diversity across non-rRNA populations. RNA-seq analysis of Escherichia coli K-12 and human intracellular total RNA showed that HAC-based normalization enriched for all non-ribosomal RNA species regardless of RNA transcript abundance or length when compared with untreated controls. Microcolumn HAC normalization generated rRNA-depleted cDNA libraries comparable to the well-established duplex specific nuclease (DSN) normalization and Ribo-Zero rRNA-depletion methods, thus establishing microscale HAC as an effective, cost saving, and non-destructive alternative normalization technique.