Correlating transcription and protein expression profiles of immune biomarkers following lipopolysaccharide exposure in lung epithelial cells.

Universal and early recognition of pathogens occurs through recognition of evolutionarily conserved pathogen associated molecular patterns (PAMPs) by innate immune receptors and the consequent secretion of cytokines and chemokines. The intrinsic complexity of innate immune signaling and associated signal transduction challenges our ability to obtain physiologically relevant, reproducible and accurate data from experimental systems. One of the reasons for the discrepancy in observed data is the choice of measurement strategy. Immune signaling is regulated by the interplay between pathogen-derived molecules with host cells resulting in cellular expression changes. However, these cellular processes are often studied by the independent assessment of either the transcriptome or the proteome. Correlation between transcription and protein analysis is lacking in a variety of studies. In order to methodically evaluate the correlation between transcription and protein expression profiles associated with innate immune signaling, we measured cytokine and chemokine levels following exposure of human cells to the PAMP lipopolysaccharide (LPS) from the Gram-negative pathogen Pseudomonas aeruginosa. Expression of 84 messenger RNA (mRNA) transcripts and 69 proteins, including 35 overlapping targets, were measured in human lung epithelial cells. We evaluated 50 biological replicates to determine reproducibility of outcomes. Following pairwise normalization, 16 mRNA transcripts and 6 proteins were significantly upregulated following LPS exposure, while only five (CCL2, CSF3, CXCL5, CXCL8/IL8, and IL6) were upregulated in both transcriptomic and proteomic analysis. This lack of correlation between transcription and protein expression data may contribute to the discrepancy in the immune profiles reported in various studies. The use of multiomic assessments to achieve a systems-level understanding of immune signaling processes can result in the identification of host biomarker profiles for a variety of infectious diseases and facilitate countermeasure design and development.

Methods to capture proteomic and metabolomic signatures from cerebrospinal fluid and serum of healthy individuals.

Discovery of reliable signatures for the empirical diagnosis of neurological diseases-both infectious and non-infectious-remains unrealized. One of the primary challenges encountered in such studies is the lack of a comprehensive database representative of a signature background that exists in healthy individuals, and against which an aberrant event can be assessed. For neurological insults and injuries, it is important to understand the normal profile in the neuronal (cerebrospinal fluid) and systemic fluids (e.g., blood). Here, we present the first comparative multi-omic human database of signatures derived from a population of 30 individuals (15 males, 15 females, 23-74 years) of serum and cerebrospinal fluid. In addition to empirical signatures, we also assigned common pathways between serum and CSF. Together, our findings provide a cohort against which aberrant signature profiles in individuals with neurological injuries/disease can be assessed-providing a pathway for comprehensive diagnostics and therapeutics discovery.

Progress Toward a Multiomic Understanding of Traumatic Brain Injury: A Review.

Traumatic brain injury (TBI) is not a single disease state but describes an array of conditions associated with insult or injury to the brain. While some individuals with TBI recover within a few days or months, others present with persistent symptoms that can cause disability, neuropsychological trauma, and even death. Understanding, diagnosing, and treating TBI is extremely complex for many reasons, including the variable biomechanics of head impact, differences in severity and location of injury, and individual patient characteristics. Because of these confounding factors, the development of reliable diagnostics and targeted treatments for brain injury remains elusive. We argue that the development of effective diagnostic and therapeutic strategies for TBI requires a deep understanding of human neurophysiology at the molecular level and that the framework of multiomics may provide some effective solutions for the diagnosis and treatment of this challenging condition. To this end, we present here a comprehensive review of TBI biomarker candidates from across the multiomic disciplines and compare them with known signatures associated with other neuropsychological conditions, including Alzheimer's disease and Parkinson's disease. We believe that this integrated view will facilitate a deeper understanding of the pathophysiology of TBI and its potential links to other neurological diseases.

Lipoprotein capture ELISA method for the sensitive detection of amphiphilic biomarkers.

Enzyme-linked immunosorbent assays (ELISAs) are widely employed for the detection of protein targets due to their ease of use, sensitivity, and potential for high-throughput analyses. However, the use of ELISAs to detect non-protein targets such as lipids and amphiphiles is complicated by the physical properties of these molecules, which affects their association with functional surfaces and recognition ligands. Here, we developed a unique lipoprotein capture ELISA in which the natural association between lipoproteins and amphiphilic molecules facilitates detection of the target biomarker in a physiologically relevant conformation. An assay to detect the glycolipid lipoarabinomannan (LAM), a cell membrane component and virulence factor associated with Mycobacterial infections, was developed as a proof of concept.

Distinguishing viruses responsible for influenza-like illness.

The many respiratory viruses that cause influenza-like illness (ILI) are reported and tracked as one entity, defined by the CDC as a group of symptoms that include a fever of 100 degrees Fahrenheit, a cough, and/or a sore throat. In the United States alone, ILI impacts 9-49 million people every year. While tracking ILI as a single clinical syndrome is informative in many respects, the underlying viruses differ in parameters and outbreak properties. Most existing models treat either a single respiratory virus or ILI as a whole. However, there is a need for models capable of comparing several individual viruses that cause respiratory illness, including ILI. To address this need, here we present a flexible model and simulations of epidemics for influenza, RSV, rhinovirus, seasonal coronavirus, adenovirus, and SARS/MERS, parameterized by a systematic literature review and accompanied by a global sensitivity analysis. We find that for these biological causes of ILI, their parameter values, timing, prevalence, and proportional contributions differ substantially. These results demonstrate that distinguishing the viruses that cause ILI will be an important aspect of future work on diagnostics, mitigation, modeling, and preparation for future pandemics.

Portable Waveguide-Based Optical Biosensor.

Rapid, on-site diagnostics allow for timely intervention and response for warfighter support, environmental monitoring, and global health needs. Portable optical biosensors are being widely pursued as a means of achieving fieldable biosensing due to the potential speed and accuracy of optical detection. We recently developed the portable engineered analytic sensor with automated sampling (PEGASUS) with the goal of developing a fieldable, generalizable biosensing platform. Here, we detail the development of PEGASUS's sensing hardware and use a test-bed system of identical sensing hardware and software to demonstrate detection of a fluorescent conjugate at 1 nM through biotin-streptavidin chemistry.

Conditions for Handling and Optimal Storage of Mycolactone.

The successful isolation of mycolactone in a laboratory or from a clinical sample relies on proper handling and storage of the toxin. Mycolactone is a light-sensitive and an amphiphilic toxin produced by Mycobacterium ulcerans. The biochemistry of the toxin makes it unstable in aqueous matrices such as blood, which causes it to self-aggregate or present in complex with carrier molecules. This biochemistry also impacts the use of the toxin in vitro, in that it tends to aggregate and stick to substrates in an aqueous environment, which alters its physiological presentation and limits its availability in a sample. Glass materials (i.e., tubes, vials, syringes, plates) should be used when possible to avoid loss of mycolactone sticking to plastic surfaces. Dark containers such as amber vials or aluminum-foil wrapped tubes should be used to avoid photodegradation of the toxin upon exposure to light. Sample storage in organic solvents is ideal for mycolactone stability and recovery; however, this is not always amenable as multiple diagnostic assays might be performed on a single sample (such as PCR or ELISA). In these cases, samples can be stored in an aqueous solution containing a small amount of detergent to enhance recovery of the toxin, and in order to avoid aggregation. Therefore, the downstream manipulations should be carefully considered prior to sample collection and storage. Here we present considerations for the optimal handling and storage of mycolactone in order to obtain quality yield of the toxin for various research and diagnostic applications.

Fast Evaluation of Viral Emerging Risks (FEVER): A computational tool for biosurveillance, diagnostics, and mutation typing of emerging viral pathogens.

Viral pathogens can rapidly evolve, adapt to novel hosts, and evade human immunity. The early detection of emerging viral pathogens through biosurveillance coupled with rapid and accurate diagnostics are required to mitigate global pandemics. However, RNA viruses can mutate rapidly, hampering biosurveillance and diagnostic efforts. Here, we present a novel computational approach called FEVER (Fast Evaluation of Viral Emerging Risks) to design assays that simultaneously accomplish: 1) broad-coverage biosurveillance of an entire group of viruses, 2) accurate diagnosis of an outbreak strain, and 3) mutation typing to detect variants of public health importance. We demonstrate the application of FEVER to generate assays to simultaneously 1) detect sarbecoviruses for biosurveillance; 2) diagnose infections specifically caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); and 3) perform rapid mutation typing of the D614G SARS-CoV-2 spike variant associated with increased pathogen transmissibility. These FEVER assays had a high in silico recall (predicted positive) up to 99.7% of 525,708 SARS-CoV-2 sequences analyzed and displayed sensitivities and specificities as high as 92.4% and 100% respectively when validated in 100 clinical samples. The D614G SARS-CoV-2 spike mutation PCR test was able to identify the single nucleotide identity at position 23,403 in the viral genome of 96.6% SARS-CoV-2 positive samples without the need for sequencing. This study demonstrates the utility of FEVER to design assays for biosurveillance, diagnostics, and mutation typing to rapidly detect, track, and mitigate future outbreaks and pandemics caused by emerging viruses.

Comparing variability in diagnosis of upper respiratory tract infections in patients using syndromic, next generation sequencing, and PCR-based methods.

Early and accurate diagnosis of respiratory pathogens and associated outbreaks can allow for the control of spread, epidemiological modeling, targeted treatment, and decision making-as is evident with the current COVID-19 pandemic. Many respiratory infections share common symptoms, making them difficult to diagnose using only syndromic presentation. Yet, with delays in getting reference laboratory tests and limited availability and poor sensitivity of point-of-care tests, syndromic diagnosis is the most-relied upon method in clinical practice today. Here, we examine the variability in diagnostic identification of respiratory infections during the annual infection cycle in northern New Mexico, by comparing syndromic diagnostics with polymerase chain reaction (PCR) and sequencing-based methods, with the goal of assessing gaps in our current ability to identify respiratory pathogens. Of 97 individuals that presented with symptoms of respiratory infection, only 23 were positive for at least one RNA virus, as confirmed by sequencing. Whereas influenza virus (n = 7) was expected during this infection cycle, we also observed coronavirus (n = 7), respiratory syncytial virus (n = 8), parainfluenza virus (n = 4), and human metapneumovirus (n = 1) in individuals with respiratory infection symptoms. Four patients were coinfected with two viruses. In 21 individuals that tested positive using PCR, RNA sequencing completely matched in only 12 (57%) of these individuals. Few individuals (37.1%) were diagnosed to have an upper respiratory tract infection or viral syndrome by syndromic diagnostics, and the type of virus could only be distinguished in one patient. Thus, current syndromic diagnostic approaches fail to accurately identify respiratory pathogens associated with infection and are not suited to capture emerging threats in an accurate fashion. We conclude there is a critical and urgent need for layered agnostic diagnostics to track known and unknown pathogens at the point of care to control future outbreaks.

ThIV-Desferrioxamine: characterization of a fluorescent bacterial probe.

Diversifying our ability to guard against emerging pathogenic threats is essential for keeping pace with global health challenges, including those presented by drug-resistant bacteria. Some modern diagnostic and therapeutic innovations to address this challenge focus on targeting methods that exploit bacterial nutrient sequestration pathways, such as the desferrioxamine (DFO) siderophore used by Staphylococcus aureus (S. aureus) to sequester FeIII. Building on recent studies that have shown DFO to be a versatile vehicle for chemical delivery, we show proof-of-principle that the FeIII sequestration pathway can be used to deliver a potential radiotherapeutic. Our approach replaces the FeIII nutrient sequestered by H4DFO+ with ThIV and made use of a common fluorophore, FITC, which we covalently bonded to DFO to provide a combinatorial probe for simultaneous chelation paired with imaging and spectroscopy, H3DFO_FITC. Combining insight provided from FITC-based imaging with characterization by NMR spectroscopy, we demonstrated that the fluorescent DFO_FITC conjugate retained the ThIV chelation properties of native H4DFO+. Fluorescence microscopy with both [Th(DFO_FITC)] and [Fe(DFO_FITC)] complexes showed similar uptake by S. aureus and increased intercellular accumulation as compared to the FITC and unchelated H3DFO_FITC controls. Collectively, these results demonstrate the potential for the newly developed H3DFO_FITC conjugate to be used as a targeting vector and bacterial imaging probe for S. aureus. The results presented within provide a framework to expand H4DFO+ and H3DFO_FITC to relevant radiotherapeutics (like 227Th).

Macrolides: From Toxins to Therapeutics.

Macrolides are a diverse class of hydrophobic compounds characterized by a macrocyclic lactone ring and distinguished by variable side chains/groups. Some of the most well characterized macrolides are toxins produced by marine bacteria, sea sponges, and other species. Many marine macrolide toxins act as biomimetic molecules to natural actin-binding proteins, affecting actin polymerization, while other toxins act on different cytoskeletal components. The disruption of natural cytoskeletal processes affects cell motility and cytokinesis, and can result in cellular death. While many macrolides are toxic in nature, others have been shown to display therapeutic properties. Indeed, some of the most well known antibiotic compounds, including erythromycin, are macrolides. In addition to antibiotic properties, macrolides have been shown to display antiviral, antiparasitic, antifungal, and immunosuppressive actions. Here, we review each functional class of macrolides for their common structures, mechanisms of action, pharmacology, and human cellular targets.

Interaction of amphiphilic lipoarabinomannan with host carrier lipoproteins in tuberculosis patients: Implications for blood-based diagnostics.

Lipoarabinomannan (LAM), an amphiphilic lipoglycan of the Mycobacterium tuberculosis cell wall, is a diagnostic target for tuberculosis. Previous work from our laboratory and others suggests that LAM is associated with host serum lipoproteins, which may in turn have implications for diagnostic assays. Our team has developed two serum assays for amphiphile detection: lipoprotein capture and membrane insertion. The lipoprotein capture assay relies on capture of the host lipoproteins, exploiting the biological association of host lipoprotein with microbial amphiphilic biomarkers to "concentrate" LAM. In contrast, the membrane insertion assay is independent of the association between pathogen amphiphiles and host lipoprotein association, and directly captures LAM based on its thermodynamic propensity for association with a supported lipid membrane, which forms the functional surface of an optical biosensor. In this manuscript, we explored the use of these assays for the detection of LAM in sera from adults whose tuberculosis status had been well-characterized using conventional microbiological tests, and endemic controls. Using the lipoprotein capture assay, LAM signal/noise ratios were >1.0 in 29/35 (83%) individuals with culture-confirmed active tuberculosis, 8/13 (62%) individuals with tuberculosis symptoms, but no positive culture for M. tuberculosis, and 0/6 (0%) symptom-free endemic controls. To evaluate serum LAM levels without bias associated with potential differences in circulating host lipoprotein concentrations between individuals, we subsequently processed available samples to liberate LAM from associated host lipoprotein assemblies followed by direct detection of the pathogen biomarker using the membrane insertion approach. Using the membrane insertion assay, signal/noise for detection of serum LAM was greater than that observed using the lipoprotein capture method for culture-confirmed TB patients (6/6), yet remained negative for controls (2/2). Taken together, these results suggest that detection of serum LAM is a promising TB diagnostic approach, but that further work is required to optimize assay performance and to decipher the implications of LAM/host lipoprotein associations for diagnostic assay performance and TB pathogenesis.

A centrifugal microfluidic cross-flow filtration platform to separate serum from whole blood for the detection of amphiphilic biomarkers.

The separation of biomarkers from blood is straightforward in most molecular biology laboratories. However, separation in resource-limited settings, allowing for the successful removal of biomarkers for diagnostic applications, is not always possible. The situation is further complicated by the need to separate hydrophobic signatures such as lipids from blood. Herein, we present a microfluidic device capable of centrifugal separation of serum from blood at the point of need with a system that is compatible with biomarkers that are both hydrophilic and hydrophobic. The cross-flow filtration device separates serum from blood as efficiently as traditional methods and retains amphiphilic biomarkers in serum for detection.

Comparative genomic and phenotypic characterization of invasive non-typhoidal Salmonella isolates from Siaya, Kenya.

Non-typhoidal Salmonella (NTS) is a major global health concern that often causes bloodstream infections in areas of the world affected by malnutrition and comorbidities such as HIV and malaria. Developing a strategy to control the emergence and spread of highly invasive and antimicrobial resistant NTS isolates requires a comprehensive analysis of epidemiological factors and molecular pathogenesis. Here, we characterize 11 NTS isolates that caused bloodstream infections in pediatric patients in Siaya, Kenya from 2003-2010. Nine isolates were identified as S. Typhimurium sequence type 313 while the other two were S. Enteritidis. Comprehensive genotypic and phenotypic analyses were performed to compare these isolates to those previously identified in sub-Saharan Africa. We identified a S. Typhimurium isolate referred to as UGA14 that displayed novel plasmid, pseudogene and resistance features as compared to other isolates reported from Africa. Notably, UGA14 is able to ferment both lactose and sucrose due to the acquisition of insertion elements on the pKST313 plasmid. These findings show for the first time the co-evolution of plasmid-mediated lactose and sucrose metabolism along with cephalosporin resistance in NTS further elucidating the evolutionary mechanisms of invasive NTS phenotypes. These results further support the use of combined genomic and phenotypic approaches to detect and characterize atypical NTS isolates in order to advance biosurveillance efforts that inform countermeasures aimed at controlling invasive and antimicrobial resistant NTS.

Pediatric Tuberculosis: The Impact of "Omics" on Diagnostics Development.

Tuberculosis (TB) is a major public health concern for all ages. However, the disease presents a larger challenge in pediatric populations, partially owing to the lack of reliable diagnostic standards for the early identification of infection. Currently, there are no biomarkers that have been clinically validated for use in pediatric TB diagnosis. Identification and validation of biomarkers could provide critical information on prognosis of disease, and response to treatment. In this review, we discuss how the "omics" approach has influenced biomarker discovery and the advancement of a next generation rapid point-of-care diagnostic for TB, with special emphasis on pediatric disease. Limitations of current published studies and the barriers to their implementation into the field will be thoroughly reviewed within this article in hopes of highlighting future avenues and needs for combating the problem of pediatric tuberculosis.

Exploring the Biocompatibility of Near-IR CuInSexS2-x/ZnS Quantum Dots for Deep-Tissue Bioimaging.

Near-infrared (NIR) emitting quantum dots (QDs) with emission in the biological transparency windows (NIR-I: 650-950 nm and NIR-II: 1000-1350 nm) are promising candidates for deep-tissue bioimaging. However, they typically contain toxic heavy metals such as cadmium, mercury, arsenic, or lead. We report on the biocompatibility of high brightness CuInSexS2-x/ZnS (CISeS/ZnS) QDs with a tunable emission covering the visible to NIR (550-1300 nm peak emission) and quantify the transmission of their photoluminescence through multiple biological components to evaluate their use as imaging agents. In general, CISeS/ZnS QDs were less cytotoxic to mouse fibroblast cells when compared with commercial CdSe/ZnS and InP/ZnS QDs. Surprisingly, InP/ZnS QDs significantly upregulated expression of apoptotic genes in mouse fibroblast cells, while cells exposed to CISeS/ZnS QDs did not. These findings provide insight into biocompatibility and cytotoxicity of CISeS/ZnS QDs that could be used for bioimaging.

A systematic review and evaluation of Zika virus forecasting and prediction research during a public health emergency of international concern.

INTRODUCTION: Epidemic forecasting and prediction tools have the potential to provide actionable information in the midst of emerging epidemics. While numerous predictive studies were published during the 2016-2017 Zika Virus (ZIKV) pandemic, it remains unknown how timely, reproducible, and actionable the information produced by these studies was. METHODS: To improve the functional use of mathematical modeling in support of future infectious disease outbreaks, we conducted a systematic review of all ZIKV prediction studies published during the recent ZIKV pandemic using the PRISMA guidelines. Using MEDLINE, EMBASE, and grey literature review, we identified studies that forecasted, predicted, or simulated ecological or epidemiological phenomena related to the Zika pandemic that were published as of March 01, 2017. Eligible studies underwent evaluation of objectives, data sources, methods, timeliness, reproducibility, accessibility, and clarity by independent reviewers. RESULTS: 2034 studies were identified, of which n = 73 met the eligibility criteria. Spatial spread, R0 (basic reproductive number), and epidemic dynamics were most commonly predicted, with few studies predicting Guillain-Barré Syndrome burden (4%), sexual transmission risk (4%), and intervention impact (4%). Most studies specifically examined populations in the Americas (52%), with few African-specific studies (4%). Case count (67%), vector (41%), and demographic data (37%) were the most common data sources. Real-time internet data and pathogen genomic information were used in 7% and 0% of studies, respectively, and social science and behavioral data were typically absent in modeling efforts. Deterministic models were favored over stochastic approaches. Forty percent of studies made model data entirely available, 29% provided all relevant model code, 43% presented uncertainty in all predictions, and 54% provided sufficient methodological detail to allow complete reproducibility. Fifty-one percent of predictions were published after the epidemic peak in the Americas. While the use of preprints improved the accessibility of ZIKV predictions by a median of 119 days sooner than journal publication dates, they were used in only 30% of studies. CONCLUSIONS: Many ZIKV predictions were published during the 2016-2017 pandemic. The accessibility, reproducibility, timeliness, and incorporation of uncertainty in these published predictions varied and indicates there is substantial room for improvement. To enhance the utility of analytical tools for outbreak response it is essential to improve the sharing of model data, code, and preprints for future outbreaks, epidemics, and pandemics.

YAP/TAZ Related BioMechano Signal Transduction and Cancer Metastasis.

Mechanoreciprocity refers to a cell's ability to maintain tensional homeostasis in response to various types of forces. Physical forces are continually being exerted upon cells of various tissue types, even those considered static, such as the brain. Through mechanoreceptors, cells sense and subsequently respond to these stimuli. These forces and their respective cellular responses are prevalent in regulating everything from embryogenic tissue-specific differentiation, programmed cell death, and disease progression, the last of which being the subject of extensive attention. Abnormal mechanical remodeling of cells can provide clues as to the pathological status of tissues. This becomes particularly important in cancer cells, where cellular stiffness has been recently accepted as a novel biomarker for cancer metastasis. Several studies have also elucidated the importance of cell stiffness in cancer metastasis, with data highlighting that a reversal of tumor stiffness has the capacity to revert the metastatic properties of cancer. In this review, we summarize our current understanding of extracellular matrix (ECM) homeostasis, which plays a prominent role in tissue mechanics. We also describe pathological disruption of the ECM, and the subsequent implications toward cancer and cancer metastasis. In addition, we highlight the most novel approaches toward understanding the mechanisms which generate pathogenic cell stiffness and provide potential new strategies which have the capacity to advance our understanding of one of human-kinds' most clinically significant medical pathologies. These new strategies include video-based techniques for structural dynamics, which have shown great potential for identifying full-field, high-resolution modal properties, in this case, as a novel application.

Modeling and Cost Benefit Analysis to Guide Deployment of POC Diagnostics for Non-typhoidal Salmonella Infections with Antimicrobial Resistance.

Invasive non-typhoidal Salmonella (NTS) is among the leading causes of blood stream infections in sub-Saharan Africa and other developing regions, especially among pediatric populations. Invasive NTS can be difficult to treat and have high case-fatality rates, in part due to emergence of strains resistant to broad-spectrum antibiotics. Furthermore, improper treatment contributes to increased antibiotic resistance and death. Point of care (POC) diagnostic tests that rapidly identify invasive NTS infection, and differentiate between resistant and non-resistant strains, may greatly improve patient outcomes and decrease resistance at the community level. Here we present for the first time a model for NTS dynamics in high risk populations that can analyze the potential advantages and disadvantages of four strategies involving POC diagnostic deployment, and the resulting impact on antimicrobial treatment for patients. Our analysis strongly supports the use of POC diagnostics coupled with targeted antibiotic use for patients upon arrival in the clinic for optimal patient and public health outcomes. We show that even the use of imperfect POC diagnostics can significantly reduce total costs and number of deaths, provided that the diagnostic gives results quickly enough that patients are likely to return or stay to receive targeted treatment.

Draft Genome Sequences of Two Staphylococcus warneri Clinical Isolates, Strains SMA0023-04 (UGA3) and SMA0670-05 (UGA28), from Siaya County Referral Hospital, Siaya, Kenya.

We report the complete draft genome sequences of two Staphylococcus warneri clinical isolates, strains SMA0023-04 (UGA3) and SMA0670-05 (UGA28), each of which contains one chromosome and at least one plasmid. Isolate SMA0023-04 (UGA3) contains tetracycline efflux major facilitator superfamily (MFS) transporter (tetK), macrolide resistance (msrC and mphC), and beta-lactamase (blaZ) genes on its plasmids.