Preliminary evidence for chaotic signatures in host-microbe interactions.

Host-microbe interactions constitute dynamical systems that can be represented by mathematical formulations that determine their dynamic nature and are categorized as deterministic, stochastic, or chaotic. Knowing the type of dynamical interaction is essential for understanding the system under study. Very little experimental work has been done to determine the dynamical characteristics of host-microbe interactions, and its study poses significant challenges. The most straightforward experimental outcome involves an observation of time to death upon infection. However, in measuring this outcome, the internal parameters and the dynamics of each particular host-microbe interaction in a population of interactions are hidden from the experimentalist. To investigate whether a time-to-death (time-to-event) data set provides adequate information for searching for chaotic signatures, we first determined our ability to detect chaos in simulated data sets of time-to-event measurements and successfully distinguished the time-to-event distribution of a chaotic process from a comparable stochastic one. To do so, we introduced an inversion measure to test for a chaotic signature in time-to-event distributions. Next, we searched for chaos in the time-to-death of Caenorhabditis elegans and Drosophila melanogaster infected with Pseudomonas aeruginosa or Pseudomonas entomophila, respectively. We found suggestions of chaotic signatures in both systems but caution that our results are preliminary and highlight the need for more fine-grained and larger data sets in determining dynamical characteristics. If validated, chaos in host-microbe interactions would have important implications for the occurrence and outcome of infectious diseases, the reproducibility of experiments in the field of microbial pathogenesis, and the prediction of microbial threats.IMPORTANCEIs microbial pathogenesis a predictable scientific field? At a time when we are dealing with coronavirus disease 2019, there is intense interest in knowing about the epidemic potential of other microbial threats and new emerging infectious diseases. To know whether microbial pathogenesis will ever be a predictable scientific field requires knowing whether a host-microbe interaction follows deterministic, stochastic, or chaotic dynamics. If randomness and chaos are absent from virulence, there is hope for prediction in the future regarding the outcome of microbe-host interactions. Chaotic systems are inherently unpredictable, although it is possible to generate short-term probabilistic models, as is done in applications of stochastic processes and machine learning to weather forecasting. Information on the dynamics of a system is also essential for understanding the reproducibility of experiments, a topic of great concern in the biological sciences. Our study finds preliminary evidence for chaotic dynamics in infectious diseases.

Chaotic signatures in host-microbe interactions.

Host-microbe interactions constitute dynamical systems that can be represented by mathematical formulations that determine their dynamic nature, and are categorized as deterministic, stochastic, or chaotic. Knowing the type of dynamical interaction is essential for understanding the system under study. Very little experimental work has been done to determine the dynamical characteristics of host-microbe interactions and its study poses significant challenges. The most straightforward experimental outcome involves an observation of time to death upon infection. However, in measuring this outcome, the internal parameters, and the dynamics of each particular host-microbe interaction in a population of interactions are hidden from the experimentalist. To investigate whether a time-to-death (time to event) dataset provides adequate information for searching for chaotic signatures, we first determined our ability to detect chaos in simulated data sets of time-to-event measurements and successfully distinguished the time-to-event distribution of a chaotic process from a comparable stochastic one. To do so, we introduced an inversion measure to test for a chaotic signature in time-to-event distributions. Next, we searched for chaos, in time-to-death of Caenorhabditis elegans and Drosophila melanogaster infected with Pseudomonas aeruginosa or Pseudomonas entomophila, respectively. We found suggestions of chaotic signatures in both systems, but caution that our results are preliminary and highlight the need for more fine-grained and larger data sets in determining dynamical characteristics. If validated, chaos in host-microbe interactions would have important implications for the occurrence and outcome of infectious diseases, the reproducibility of experiments in the field of microbial pathogenesis and the prediction of microbial threats.

ABCDs of the Relative Contributions of Pseudomonas aeruginosa Quorum Sensing Systems to Virulence in Diverse Nonvertebrate Hosts.

Pseudomonas aeruginosa is an opportunistic bacterial pathogen that exhibits pathogenicity in an unusually broad range of plants and animals, and it is of interest to study the roles of particular virulence-related factors in diverse hosts. The production of many P. aeruginosa virulence factors is under the control of a quorum sensing (QS) signaling network, which has three interconnected branches that engage in intricate cross talk: Las, Rhl, and MvfR. Because there has been no systematic comparison of the roles of the three QS systems in mediating P. aeruginosa virulence in various hosts, we compared the virulence of wild-type (WT) P. aeruginosa PA14 and a set of isogenic PA14 QS in-frame deletion mutants in four selected hosts, the reference plant Arabidopsis thaliana (Arabidopsis), the crop plant Brassica napus (canola), the nematode Caenorhabditis elegans, and the fruit fly Drosophila melanogaster. The first letters of the selected host genera, A, B, C, and D, inspired the title of this article and indicate that this work lays the groundwork for future elucidation of the specific roles of each QS branch in mediating virulence in diverse hosts. IMPORTANCE In this study, we performed a systematic comparison of the virulence of WT P. aeruginosa and QS mutants in selected hosts and conditions. This work represents an important contribution to the long-term goal of unraveling the entangled roles of different branches of the P. aeruginosa QS network in different hosts and will serve as a valuable resource for the field of host-pathogen interactions.

Landscape of Biomarkers in Non-small Cell Lung Cancer Using Comprehensive Genomic Profiling and PD-L1 Immunohistochemistry.

Comprehensive genomic profiling (CGP) and immunohistochemistry (IHC) are important biomarker tools used for patients with non-small cell lung cancer (NSCLC) given the expanding number of standard-of-care therapies that require companion diagnostic testing. We examined 9450 NSCLC real-world patient samples that underwent both CGP and programmed death-ligand 1 (PD-L1) IHC to understand the biomarker landscape in this patient cohort. By assessing National Comprehensive Cancer Network (NCCN)-recommended biomarkers including genomic alterations, tumor mutational burden (≥10 mutations/Mb cut-off), and PD-L1 expression (Tumor Proportion Score (TPS) ≥ 50% cut-off), we show that CGP + PD-L1 IHC yielded potentially actionable results for 70.5% of the 9,450 patients with NSCLC. Among the remaining 29.5% (2,789/9,450) of patients, 86.7% (2,419/2,789) were potentially eligible for another biomarker-associated therapy and/or clinical trial based on their genomic profile. In addition, in the PD-L1TPS≥50% disease subset, BRAF mutations, MET mutations, MET amplifications, and KRAS mutations were significantly enriched; and in the PD-L1TPS<50%, EGFR mutations, ERBB2 mutations, STK11 mutations, and KEAP1 mutations were enriched. These findings highlight the improved clinical utility of combining CGP with IHC to expand the biomarker-guided therapeutic options available for patients with NSCLC, relative to single biomarker testing alone.

Clinicopathologic and Genomic Characterization of PD-L1 Positive Urothelial Carcinomas.

INTRODUCTION: Pembrolizumab was approved with an accompanying companion diagnostic (CDx) assay (PD-L1 DAKO 22C3) for urothelial carcinoma (UC). In this study, we further characterize the clinicopathologic and genomic features of UC that are programmed death-ligand 1 (PD-L1) positive. MATERIALS AND METHODS: The cohort of this study consisted of a total of 528 consecutive UC patients with PD-L1 immunohistochemistry (IHC) and comprehensive genomic profiling (CGP). All PD-L1 IHC testing was performed using the DAKO 22C3 CDx assay for UC. PD-L1 positivity was determined at a combined positive score ≥ 10. RESULTS: A total of 44.5% (235/528) patients with UC were PD-L1positive . A lower PD-L1 positivity rate was detected in primary (42.3%, 148/350) versus metastatic sites (48.9%, 87/178). PD-L1 positivity was dependent on the location of the metastatic sites. CGP revealed PD-L1positive patients had more frequent genomic alterations (GAs) in TP53 (p = .006) and RB1 (p = .003) and less frequent GAs in FGFR3 (p = .001) and MTAP (p = .028). The APOBEC mutational signature and tumor mutational burden (TMB)-high were more common in PD-L1positive patients. By testing patients with UC with CGP, in addition to PD-L1 IHC, an additional 97 patients (18.4%) in the total cohort were eligible for immunotherapy based on TMB status. CONCLUSION: PD-L1positive and PD-L1negative urothelial carcinomas are genomically different. Also, our study provides the framework for future clinical investigation with regard to specimen site selection for PD-L1 testing as well as candidate biomarker genomic alterations that may predict for better response or lack of response to immune checkpoint inhibitors. IMPLICATIONS FOR PRACTICE: In this study, a higher prevalence of TP53 and RB1 alterations and APOBEC mutational signatures in the PD-L1positive urothelial carcinoma disease subset and enrichment of FGFR3 alterations in the PD-L1negative disease subset were found. These data provide the basis for future investigation into the role of these genomic changes as positive and negative predictors of immunotherapy response. Also, differences wer seen in PD-L1 positivity based on the collection site of the sample, which can provide a framework for future clinical trial design and could influence sample selection for PD-L1 testing in patients with urothelial carcinoma when multiple samples are available.

Biomarkers in Breast Cancer: An Integrated Analysis of Comprehensive Genomic Profiling and PD-L1 Immunohistochemistry Biomarkers in 312 Patients with Breast Cancer.

BACKGROUND: We examined the current biomarker landscape in breast cancer when programmed death-ligand 1 (PD-L1) testing is integrated with comprehensive genomic profiling (CGP). MATERIAL AND METHODS: We analyzed data from samples of 312 consecutive patients with breast carcinoma tested with both CGP and PD-L1 (SP142) immunohistochemistry (IHC) during routine clinical care. These samples were stratified into hormone receptor positive (HR+)/human epidermal growth factor receptor negative (HER2-; n = 159), HER2-positive (n = 32), and triple-negative breast cancer (TNBC) cohorts (n = 121). RESULTS: We found that in the TNBC cohort, 43% (52/121) were immunocyte PD-L1-positive, and in the HR+/HER2- cohort, 30% (48/159) had PIK3CA companion diagnostics mutations, and hence were potentially eligible for atezolizumab plus nab-paclitaxel or alpelisib plus fulvestrant, respectively. Of the remaining 212 patients, 10.4% (22/212) had a BRCA1/2 mutation, which, if confirmed by germline testing, would allow olaparib plus talazoparib therapy. Of the remaining 190 patients, 169 (88.9%) were positive for another therapy-associated marker or a marker that would potentially qualify the patient for a clinical trial. In addition, we examined the relationship between immunocyte PD-L1 positivity and different tumor mutation burden (TMB) cutoffs and found that when a TMB cutoff of ≥9 mutations per Mb was applied (cutoff determined based on prior publication), 11.6% (14/121) patients were TMB ≥9 mutations/Mb and of these, TMB ≥9 mutations per Mb, 71.4% (10/14) were also positive for PD-L1 IHC. CONCLUSION: Our integrated PD-L1 and CGP methodology identified 32% of the tested patients as potentially eligible for at least one of the two new Food and Drug Administration approved therapies, atezolizumab or alpelisib, and an additional 61.2% (191/312) had other biomarker-guided potential therapeutic options. IMPLICATIONS FOR PRACTICE: This integrated programmed death-ligand 1 immunohistochemistry and comprehensive genomic profiling methodology identified 32% of the tested patients as eligible for at least one of the two new Food and Drug Administration-approved therapies, atezolizumab or alpelisib, and an additional 61.2% (191/312) had other biomarker-guided potential therapeutic options. These findings suggest new research opportunities to evaluate the predictive utility of other commonly seen PIK3CA mutations in hormone receptor-positive breast cancers and to standardize tumor mutation burden cutoffs to evaluate its potentially predictive role in triple-negative breast cancer.

Measurements of Innate Immune Function in C. elegans.

The microscopic nematode Caenorhabditis elegans has emerged as a powerful system to characterize evolutionarily ancient mechanisms of pathogen sensing, innate immune activation, and protective host responses. Experimentally, C. elegans can be infected with a wide variety of human pathogens, as well as with natural pathogens of worms that were isolated from wild-caught nematodes. Here, we focus on an experimental model of bacterial pathogenesis that utilizes the human opportunistic bacterial pathogen Pseudomonas aeruginosa and present an algorithm that can be used to study mechanisms of immune function in nematodes. An initial comparison of the susceptibility of a C. elegans mutant to P. aeruginosa infection with its normal lifespan permits an understanding of a mutant's effect on pathogen susceptibility in the context of potential pleotropic consequences on general worm fitness. Assessing the behavior of nematodes in the presence of P. aeruginosa can also help determine if a gene of interest modulates pathogen susceptibility by affecting the host's ability to avoid a pathogen. In addition, quantification of the pathogen load in the C. elegans intestine during infection, characterization of immune effector transcription that are regulated by host defense pathways and an initial assessment of tissue specificity of immune gene function can refine hypotheses about the mechanism of action of a gene of interest. Together, these protocols offer one approach to characterize novel host defense mechanisms in a simple metazoan host.

Tribbles ortholog NIPI-3 and bZIP transcription factor CEBP-1 regulate a Caenorhabditis elegans intestinal immune surveillance pathway.

BACKGROUND: Many pathogens secrete toxins that target key host processes resulting in the activation of immune pathways. The secreted Pseudomonas aeruginosa toxin Exotoxin A (ToxA) disrupts intestinal protein synthesis, which triggers the induction of a subset of P. aeruginosa-response genes in the nematode Caenorhabditis elegans. RESULTS: We show here that one ToxA-induced C. elegans gene, the Tribbles pseudokinase ortholog nipi-3, is essential for host survival following exposure to P. aeruginosa or ToxA. We find that NIPI-3 mediates the post-developmental expression of intestinal immune genes and proteins and primarily functions in parallel to known immune pathways, including p38 MAPK signaling. Through mutagenesis screening, we identify mutants of the bZIP C/EBP transcription factor cebp-1 that suppress the hypersusceptibility defects of nipi-3 mutants. CONCLUSIONS: NIPI-3 is a negative regulator of CEBP-1, which in turn negatively regulates protective immune mechanisms. This pathway represents a previously unknown innate immune signaling pathway in intestinal epithelial cells that is involved in the surveillance of cellular homeostasis. Because NIPI-3 and CEBP-1 are also essential for C. elegans development, NIPI-3 is analogous to other key innate immune signaling molecules such as the Toll receptors in Drosophila that have an independent role during development.

The evolutionarily conserved mediator subunit MDT-15/MED15 links protective innate immune responses and xenobiotic detoxification.

Metazoans protect themselves from environmental toxins and virulent pathogens through detoxification and immune responses. We previously identified a small molecule xenobiotic toxin that extends survival of Caenorhabditis elegans infected with human bacterial pathogens by activating the conserved p38 MAP kinase PMK-1 host defense pathway. Here we investigate the cellular mechanisms that couple activation of a detoxification response to innate immunity. From an RNAi screen of 1,420 genes expressed in the C. elegans intestine, we identified the conserved Mediator subunit MDT-15/MED15 and 28 other gene inactivations that abrogate the induction of PMK-1-dependent immune effectors by this small molecule. We demonstrate that MDT-15/MED15 is required for the xenobiotic-induced expression of p38 MAP kinase PMK-1-dependent immune genes and protection from Pseudomonas aeruginosa infection. We also show that MDT-15 controls the induction of detoxification genes and functions to protect the host from bacteria-derived phenazine toxins. These data define a central role for MDT-15/MED15 in the coordination of xenobiotic detoxification and innate immune responses.

Uptake of extracellular double-stranded RNA by SID-2.

Ingested dsRNAs trigger RNA interference (RNAi) in many invertebrates, including the nematode Caenorhabditis elegans. Here we show that the C. elegans apical intestinal membrane protein SID-2 is required in C. elegans for the import of ingested dsRNA and that, when expressed in Drosophila S2 cells, SID-2 enables the uptake of dsRNAs. SID-2-dependent dsRNA transport requires an acidic extracellular environment and is selective for dsRNAs with at least 50 base pairs. Through structure-function analysis, we identify several SID-2 regions required for this activity, including three extracellular, positively charged histidines. Finally, we find that SID-2-dependent transport is inhibited by drugs that interfere with vesicle transport. Therefore, we propose that environmental dsRNAs are imported from the acidic intestinal lumen by SID-2 via endocytosis and are released from internalized vesicles in a secondary step mediated by the dsRNA channel SID-1. Similar multistep mechanisms may underlie the widespread observations of environmental RNAi.

Host translational inhibition by Pseudomonas aeruginosa Exotoxin A Triggers an immune response in Caenorhabditis elegans.

Intestinal epithelial cells are exposed to both innocuous and pathogenic microbes, which need to be distinguished to mount an effective immune response. To understand the mechanisms underlying pathogen recognition, we investigated how Pseudomonas aeruginosa triggers intestinal innate immunity in Caenorhabditis elegans, a process independent of Toll-like pattern recognition receptors. We show that the P. aeruginosa translational inhibitor Exotoxin A (ToxA), which ribosylates elongation factor 2 (EF2), upregulates a significant subset of genes normally induced by P. aeruginosa. Moreover, immune pathways involving the ATF-7 and ZIP-2 transcription factors, which protect C. elegans from P. aeruginosa, are required for preventing ToxA-mediated lethality. ToxA-responsive genes are not induced by enzymatically inactive ToxA protein but can be upregulated independently of ToxA by disruption of host protein translation. Thus, C. elegans has a surveillance mechanism to recognize ToxA through its effect on protein translation rather than by direct recognition of either ToxA or ribosylated EF2.