Supplementary Methods from Voltage-Gated Na⁺ Channel <i>SCN5A</i> Is a Key Regulator of a Gene Transcriptional Network That Controls Colon Cancer Invasion

Supplementary Figure 4 from Voltage-Gated Na+ Channel SCN5A Is a Key Regulator of a Gene Transcriptional Network That Controls Colon Cancer Invasion

Supplementary Figure 2 from Voltage-Gated Na⁺ Channel <i>SCN5A</i> Is a Key Regulator of a Gene Transcriptional Network That Controls Colon Cancer Invasion

Supplementary Figure 3 from Voltage-Gated Na+ Channel SCN5A Is a Key Regulator of a Gene Transcriptional Network That Controls Colon Cancer Invasion

Supplementary Table 1 from Voltage-Gated Na+ Channel SCN5A Is a Key Regulator of a Gene Transcriptional Network That Controls Colon Cancer Invasion

Supplementary Table 2 from Voltage-Gated Na+ Channel SCN5A Is a Key Regulator of a Gene Transcriptional Network That Controls Colon Cancer Invasion

Supplementary Figure 3 from Voltage-Gated Na+ Channel SCN5A Is a Key Regulator of a Gene Transcriptional Network That Controls Colon Cancer Invasion

Supplementary Methods from Voltage-Gated Na+ Channel SCN5A Is a Key Regulator of a Gene Transcriptional Network That Controls Colon Cancer Invasion

Prophylactic or therapeutic antibiotic use along with chemotherapy treatment potentially has a long-standing adverse effect on the resident gut microbiota. We have established a case-control cohort of 32 pediatric and adolescent acute lymphoblastic leukemia (ALL) patients and 25 healthy siblings (sibling controls) to assess the effect of chemotherapy as well as antibiotic prophylaxis on the gut microbiota. We observe that the microbiota diversity and richness of the ALL group is significantly lower than that of the control group at diagnosis and during chemotherapy. The microbiota diversity is even lower in antibiotics-exposed ALL patients. Although the gut microbial diversity tends to stabilize after 1-year post-chemotherapy, their abundances were altered because of chemotherapy and prophylactic antibiotic treatments. Specifically, the abundances of mucolytic gram-positive anaerobic bacteria, including Ruminococcus gnavus and Ruminococcus torques, tended to increase during the chemotherapy regimen and continued to be elevated 1 year beyond the initiation of chemotherapy. This dysbiosis may contribute to the development of gastrointestinal complications in ALL children following chemotherapy. These findings set the stage to further understand the role of the gut microbiome dynamics in ALL patients and their potential role in alleviating some of the adverse side effects of chemotherapy and antibiotics use in immunocompromised children.

The skin is a complex living ecosystem harboring diverse microbial communities. Its highly variable properties and influence of intrinsic and extrinsic factors creates unique microenvironments where niche-specific microbes thrive. As part of the skin, hair supports its own microbial habitat that is also intra and inter-personal variable. This little explored substrate has significant potential in forensics microbiome research due to the unique signatures that are available on an individual. To further investigate this, we explored the hair microbiota from scalp and pubic regions in healthy adults to investigate how the hair shaft microenvironment varies microbially. Our results suggest that there are distinct differences between the microbial communities identified on hair shafts originating from different parts of the body. The taxonomic composition of the communities from different hair sources are most reminiscent of those identified from their associated cutaneous region. We further demonstrate that the hair microbiota varies by geographical origin and has the potential to be used to predict the source location of the hair.

Most antibiotics were discovered by screening soil actinomycetes, but the efficiency of the discovery platform collapsed in the 1960s. By now, more than 3000 antibiotics have been described and most of the current discovery effort is focused on the rediscovery of known compounds, making the approach impractical. The last marketed broad-spectrum antibiotics discovered were daptomycin, linezolid, and fidaxomicin. The current state of the art in the development of new anti-infectives is a non-existent pipeline in the absence of a discovery platform. This is particularly troubling given the emergence of pan-resistant pathogens. The current practice in dealing with the problem of the background of known compounds is to use chemical dereplication of extracts to assess the relative novelty of a compound it contains. Dereplication typically requires scale-up, extraction, and often fractionation before an accurate mass and structure can be produced by MS analysis in combination with 2D NMR. Here, we describe a transcriptome analysis approach using RNA sequencing (RNASeq) to identify promising novel antimicrobial compounds from microbial extracts. Our pipeline permits identification of antimicrobial compounds that produce distinct transcription profiles using unfractionated cell extracts. This efficient pipeline will eliminate the requirement for purification and structure determination of compounds from extracts and will facilitate high-throughput screen of cell extracts for identification of novel compounds.

Viral infections such as influenza have been shown to predispose hosts to increased colonization of the respiratory tract by pathogenic bacteria and secondary bacterial pneumonia. To examine how viral infections and host antiviral immune responses alter the upper respiratory microbiota, we analyzed nasal bacterial composition by 16S ribosomal RNA (rRNA) gene sequencing in healthy adults at baseline and at 1 to 2 weeks and 4 to 6 weeks following instillation of live attenuated influenza vaccine or intranasal sterile saline. A subset of these samples was submitted for microarray host gene expression profiling.

Ubiquity-ubiquity plot contrasting the ubiquities of a number of selected taxa, across a range of relative abundances between visits 1 and 2 in the control group as ascertained by hypervariable region V3–V5 sequencing. Only OTUs with a relative abundance greater than 0.5 % and change in ubiquity greater than 20 % were included in this plot. OTUs that aligned to the right of the diagonal were more ubiquitous during visit 1, while those to the left were more ubiquitous at visit 2.

Staphylococcus aureus is a human pathogen responsible for substantial morbidity and mortality through its ability to cause a number of human infections including bacteremia, pneumonia and soft tissue infections. Of great concern is the emergence and dissemination of methicillin–resistant Staphylococcus aureus strains (MRSA) that are resistant to nearly all β-lactams. The emergence of the USA300 MRSA genetic background among community associated S. aureus infections (CA-MRSA) in the USA was followed by the disappearance of USA400 CA-MRSA isolates.

The potential for commensal microorganisms indigenous to a host (the 'microbiome' or 'microbiota') to alter infection outcome by influencing host-pathogen interplay is largely unknown. We used a multi-omics "systems" approach, incorporating proteomics, metabolomics, glycomics, and metagenomics, to explore the molecular interplay between the murine host, the pathogen Salmonella enterica serovar Typhimurium (S. Typhimurium), and commensal gut microorganisms during intestinal infection with S. Typhimurium. We find proteomic evidence that S. Typhimurium thrives within the infected 129/SvJ mouse gut without antibiotic pre-treatment, inducing inflammation and disrupting the intestinal microbiome (e.g., suppressing Bacteroidetes and Firmicutes while promoting growth of Salmonella and Enterococcus). Alteration of the host microbiome population structure was highly correlated with gut environmental changes, including the accumulation of metabolites normally consumed by commensal microbiota. Finally, the less characterized phase of S. Typhimurium's lifecycle was investigated, and both proteomic and glycomic evidence suggests S. Typhimurium may take advantage of increased fucose moieties to metabolize fucose while growing in the gut. The application of multiple omics measurements to Salmonella-induced intestinal inflammation provides insights into complex molecular strategies employed during pathogenesis between host, pathogen, and the microbiome.

Macrophages are central players in immune response, manifesting divergent phenotypes to control inflammation and innate immunity through release of cytokines and other signaling factors. Recently, the focus on metabolism has been reemphasized as critical signaling and regulatory pathways of human pathophysiology, ranging from cancer to aging, often converge on metabolic responses. Here, we used genome‐scale modeling and multi‐omics (transcriptomics, proteomics, and metabolomics) analysis to assess metabolic features that are critical for macrophage activation. We constructed a genome‐scale metabolic network for the RAW 264.7 cell line to determine metabolic modulators of activation. Metabolites well‐known to be associated with immunoactivation (glucose and arginine) and immunosuppression (tryptophan and vitamin D3) were among the most critical effectors. Intracellular metabolic mechanisms were assessed, identifying a suppressive role for de‐novo nucleotide synthesis. Finally, underlying metabolic mechanisms of macrophage activation are identified by analyzing multi‐omic data obtained from LPS‐stimulated RAW cells in the context of our flux‐based predictions. Our study demonstrates metabolism's role in regulating activation may be greater than previously anticipated and elucidates underlying connections between activation and metabolic effectors. Genome‐scale metabolic network reconstruction and analysis of the murine leukemic macrophage cell line RAW 264.7 reveal a complementary relationship between how known metabolic immunomodulators are biochemically processed and their role in macrophage activation. Genome‐scale metabolic network reconstruction and analysis of the murine leukemic macrophage cell line RAW 264.7 reveal a complementary relationship between how known metabolic immunomodulators are biochemically processed and their role in macrophage activation.

The underlying mechanisms that lead to dramatic differences between closely related pathogens are not always readily apparent. For example, the genomes of Yersinia pestis (YP) the causative agent of plague with a high mortality rate and Yersinia pseudotuberculosis (YPT) an enteric pathogen with a modest mortality rate are highly similar with some species specific differences; however the molecular causes of their distinct clinical outcomes remain poorly understood. In this study, a temporal multi-omic analysis of YP and YPT at physiologically relevant temperatures was performed to gain insights into how an acute and highly lethal bacterial pathogen, YP, differs from its less virulent progenitor, YPT. This analysis revealed higher gene and protein expression levels of conserved major virulence factors in YP relative to YPT, including the Yop virulon and the pH6 antigen. This suggests that adaptation in the regulatory architecture, in addition to the presence of unique genetic material, may contribute to the increased pathogenecity of YP relative to YPT. Additionally, global transcriptome and proteome responses of YP and YPT revealed conserved post-transcriptional control of metabolism and the translational machinery including the modulation of glutamate levels in Yersiniae. Finally, the omics data was coupled with a computational network analysis, allowing an efficient prediction of novel Yersinia virulence factors based on gene and protein expression patterns.

Genome sequencing continues to be a rapidly evolving technology, yet most downstream aspects of genome annotation pipelines remain relatively stable or are even being abandoned. The annotation process is now performed almost exclusively in an automated fashion to balance the large number of sequences generated. One possible way of reducing errors inherent to automated computational annotations is to apply data from omics measurements (i.e. transcriptional and proteomic) to the un-annotated genome with a proteogenomic-based approach. Here, the concept of annotation refinement has been extended to include a comparative assessment of genomes across closely related species. Transcriptomic and proteomic data derived from highly similar pathogenic Yersiniae (Y. pestis CO92, Y. pestis Pestoides F, and Y. pseudotuberculosis PB1/+) was used to demonstrate a comprehensive comparative omic-based annotation methodology. Peptide and oligo measurements experimentally validated the expression of nearly 40% of each strain's predicted proteome and revealed the identification of 28 novel and 68 incorrect (i.e., observed frameshifts, extended start sites, and translated pseudogenes) protein-coding sequences within the three current genome annotations. Gene loss is presumed to play a major role in Y. pestis acquiring its niche as a virulent pathogen, thus the discovery of many translated pseudogenes, including the insertion-ablated argD, underscores a need for functional analyses to investigate hypotheses related to divergence. Refinements included the discovery of a seemingly essential ribosomal protein, several virulence-associated factors, a transcriptional regulator, and many hypothetical proteins that were missed during annotation.

Oxygen sensing and redox signaling significantly affect bacterial physiology and host-pathogen interaction. Here we show that a Staphylococcus aureus two-component system, AirSR (anaerobic iron-sulfur cluster-containing redox sensor regulator, formerly YhcSR), responds to oxidation signals (O(2), H(2)O(2), NO, etc) by using a redox-active [2Fe-2S] cluster in the sensor kinase AirS. Mutagenesis studies demonstrate that the [2Fe-2S] cluster is essential for the kinase activity of AirS. We have also discovered that a homologue of IscS (SA1450) in S. aureus is active as a cysteine desulfurase, which enables the in vitro reconstitution of the [2Fe-2S] cluster in AirS. Phosphorylation assays show that the oxidized AirS with a [2Fe-2S](2+) cluster is the fully active form of the kinase but not the apo-AirS nor the reduced AirS possessing a [2Fe-2S](+) cluster. Overoxidation by prolonged exposure to O(2) or contact with H(2)O(2) or NO led to inactivation of AirS. Transcriptome analysis revealed that mutation of airR impacts the expression of ~355 genes under anaerobic conditions. Moreover, the mutant strain displayed increased resistance toward H(2)O(2), vancomycin, norfloxacin, and ciprofloxacin under anaerobic conditions. Together, our results show that S. aureus AirSR is a redox-dependent global regulatory system that plays important roles in gene regulation using a redox active Fe-S cluster under O(2)-limited conditions.