Single-pulse transcranial magnetic stimulation for assessment of motor development in infants with early brain injury.

INTRODUCTION: Single-pulse transcranial magnetic stimulation (TMS) has many applications for pediatric clinical populations, including infants with perinatal brain injury. As a noninvasive neuromodulation tool, single-pulse TMS has been used safely in infants and children to assess corticospinal integrity and circuitry patterns. TMS may have important applications in early detection of atypical motor development or cerebral palsy. AREAS COVERED: The authors identified and summarized relevant studies incorporating TMS in infants, including findings related to corticospinal development and circuitry, motor cortex localization and mapping, and safety. This special report also describes methodologies and safety considerations related to TMS assessment in infants, and discusses potential applications related to diagnosis of cerebral palsy and early intervention. EXPERT OPINION: Single-pulse TMS has demonstrated safety and feasibility in infants with perinatal brain injury and may provide insight into neuromotor development and potential cerebral palsy diagnosis. Additional research in larger sample sizes will more fully evaluate the utility of TMS biomarkers in early diagnosis and intervention. Methodological challenges to performing TMS in infants and technical/equipment limitations require additional consideration and innovation toward clinical implementation. Future research may explore use of noninvasive neuromodulation techniques as an intervention in younger children with perinatal brain injury to improve motor outcomes.

Single pulse transcranial magnetic stimulation (TMS) is a safe and noninvasive way to study brain activity in infants and children who have experienced brain injuries around the time of birth. Infants who have had an early brain injury may develop cerebral palsy, a developmental disability that affects movement. TMS uses a device that gives single pulses of energy to activate specific areas of the brain. This can be used to study how the brain connects to the muscles in the body through paths or 'tracts.' TMS helps researchers understand the development of the tracts and the potential need for therapy. This article reviews research studies that used TMS in infants and explains how TMS can be used to assess brain development. It also reviews safety considerations and challenges related to using TMS in infants. TMS could be a valuable tool for early diagnosis of cerebral palsy and could also help guide treatments for infants with brain injuries. However, more research is needed, using larger groups of infants, to potentially expand the use of TMS in clinical practice. Future directions include developing infant-specific research tools and using noninvasive brain stimulation to improve recovery for infants with brain injuries.

Evaluation of putative signatures of consciousness using specific definitions of responsiveness, connectedness, and consciousness.

BACKGROUND: Understanding the neural correlates of consciousness has important ramifications for the theoretical understanding of consciousness and for clinical anaesthesia. A major limitation of prior studies is the use of responsiveness as an index of consciousness. We identified a collection of measures derived from unresponsive subjects and more specifically their association with consciousness (any subjective experience) or connectedness (specific experience of environmental stimuli). METHODS: Using published data generated through the UNderstanding Consciousness Connectedness and Intra-Operative Unresponsiveness Study (NCT03284307), we evaluated 10 previously published resting-state EEG-based measures that were derived using unresponsiveness as a proxy for unconsciousness. Measures were tested across dexmedetomidine and propofol sedation and natural sleep. These markers represent the complexity, connectivity, cross-frequency coupling, graph theory, and power spectrum measures. RESULTS: Although many of the proposed markers were associated with consciousness per se (reported subjective experience), none were specific to consciousness alone; rather, each was also associated with connectedness (i.e. awareness of the environment). In addition, multiple markers showed no association with consciousness and were associated only with connectedness. Of the markers tested, loss of normalised-symbolic transfer entropy (front to back) was associated with connectedness across all three experimental conditions, whereas the transition from disconnected consciousness to unconsciousness was associated with significant decreases in permutation entropy and spectral exponent (P<0.05 for all conditions). CONCLUSIONS: None of the proposed EEG-based neural correlates of unresponsiveness corresponded solely to consciousness, highlighting the need for a more conservative use of the term (un)consciousness when assessing unresponsive participants. CLINICAL TRIAL REGISTRATION: NCT03284307.

Dynamic causal modelling of auditory surprise during disconnected consciousness: The role of feedback connectivity.

The neural mechanisms through which individuals lose sensory awareness of their environment during anesthesia remains poorly understood despite being of vital importance to the field. Prior research has not distinguished between sensory awareness of the environment (connectedness) and consciousness itself. In the current study, we investigated the neural correlates of sensory awareness by contrasting neural responses to an auditory roving oddball paradigm during consciousness with sensory awareness (connected consciousness) and consciousness without sensory awareness (disconnected consciousness). These states were captured using a serial awakening paradigm with the sedative alpha2 adrenergic agonist dexmedetomidine, chosen based on our published hypothesis that suppression of noradrenaline signaling is key to induce a state of sensory disconnection. High-density electroencephalography was recorded from 18 human subjects before and after administration of dexmedetomidine. By investigating event-related potentials and taking advantage of advances in Dynamic Causal Modeling (DCM), we assessed alterations in effective connectivity between nodes of a previously established auditory processing network. We found that during disconnected consciousness, the scalp-level response to standard tones produced a P3 response that was absent during connected consciousness. This P3 response resembled the response to oddball tones seen in connected consciousness. DCM showed that disconnection produced increases in standard tone feedback signaling throughout the auditory network. Simulation analyses showed that these changes in connectivity, most notably the increase in feedback from right superior temporal gyrus to right A1, can explain the new P3 response. Together these findings show that during disconnected consciousness there is a disruption of normal predictive coding processes, so that all incoming auditory stimuli become similarly surprising.

Distinct EEG signatures differentiate unconsciousness and disconnection during anaesthesia and sleep.

BACKGROUND: How conscious experience becomes disconnected from the environment, or disappears, across arousal states is unknown. We sought to identify the neural correlates of sensory disconnection and unconsciousness using a novel serial awakening paradigm. METHODS: Volunteers were recruited for sedation with dexmedetomidine i.v., propofol i.v., or natural sleep with high-density EEG monitoring and serial awakenings to establish whether subjects were in states of disconnected consciousness or unconsciousness in the preceding 20 s. The primary outcome was classification of conscious states by occipital delta power (0.5-4 Hz). Secondary analyses included derivation (dexmedetomidine) and validation (sleep/propofol) studies of EEG signatures of conscious states. RESULTS: Occipital delta power differentiated disconnected and unconscious states for dexmedetomidine (area under the curve [AUC] for receiver operating characteristic 0.605 [95% confidence interval {CI}: 0.516; 0.694]) but not for sleep/propofol (AUC 0.512 [95% CI: 0.380; 0.645]). Distinct source localised signatures of sensory disconnection (AUC 0.999 [95% CI: 0.9954; 1.0000]) and unconsciousness (AUC 0.972 [95% CI: 0.9507; 0.9879]) were identified using support vector machine classification of dexmedetomidine data. These findings generalised to sleep/propofol (validation data set: sensory disconnection [AUC 0.743 {95% CI: 0.6784; 0.8050}]) and unconsciousness (AUC 0.622 [95% CI: 0.5176; 0.7238]). We identified that sensory disconnection was associated with broad spatial and spectral changes. In contrast, unconsciousness was associated with focal decreases in activity in anterior and posterior cingulate cortices. CONCLUSIONS: These findings may enable novel monitors of the anaesthetic state that can distinguish sensory disconnection and unconsciousness, and these may provide novel insights into the biology of arousal. CLINICAL TRIAL REGISTRATION: NCT03284307.

Postoperative delirium and changes in the blood-brain barrier, neuroinflammation, and cerebrospinal fluid lactate: a prospective cohort study.

BACKGROUND: Case-control studies have associated delirium with blood-brain barrier (BBB) permeability. However, this approach cannot determine whether delirium is attributable to high pre-existing permeability or to perioperative changes. We tested whether perioperative changes in cerebrospinal fluid/plasma albumin ratio (CPAR) and plasma S100B were associated with delirium severity. METHODS: Participants were recruited to two prospective cohort studies of non-intracranial surgery (NCT01980511, NCT03124303, and NCT02926417). Delirium severity was assessed using the Delirium Rating Scale-98. Delirium incidence was diagnosed with the 3D-Confusion Assessment Method (3D-CAM) or CAM-ICU (CAM for the ICU). CSF samples from 25 patients and plasma from 78 patients were analysed for albumin and S100B. We tested associations between change in CPAR (n=11) and S100B (n=61) and delirium, blood loss, CSF interleukin-6 (IL-6), and CSF lactate. RESULTS: The perioperative increase in CPAR and S100B correlated with delirium severity (CPAR ρ=0.78, P=0.01; S100B ρ=0.41, P<0.001), delirium incidence (CPAR P=0.012; S100B P<0.001) and CSF IL-6 (CPAR ρ=0.66 P=0.04; S100B ρ=0.75, P=0.025). Linear mixed-effect analysis also showed that decreased levels of S100B predicted recovery from delirium symptoms (P=0.001). Linear regression demonstrated that change in plasma S100B was independently associated with surgical risk, cardiovascular surgery, blood loss, and hypotension. Blood loss also correlated with CPAR (ρ=0.64, P=0.04), S100B (ρ=0.70, P<0.001), CSF lactate (R=0.81, P=0.01), and peak delirium severity (ρ=0.36, P=0.01). CONCLUSION: Postoperative delirium is associated with a breakdown in the BBB. This increased permeability is dynamic and associated with a neuroinflammatory and lactate response. Strategies to mitigate blood loss may protect the BBB.

Predictive Feedback, Early Sensory Representations, and Fast Responses to Predicted Stimuli Depend on NMDA Receptors.

Learned associations between stimuli allow us to model the world and make predictions, crucial for efficient behavior (e.g., hearing a siren, we expect to see an ambulance and quickly make way). While there are theoretical and computational frameworks for prediction, the circuit and receptor-level mechanisms are unclear. Using high-density EEG, Bayesian modeling, and machine learning, we show that inferred "causal" relationships between stimuli and frontal alpha activity account for reaction times (a proxy for predictions) on a trial-by-trial basis in an audiovisual delayed match-to-sample task which elicited predictions. Predictive ß feedback activated sensory representations in advance of predicted stimuli. Low-dose ketamine, an NMDAR blocker, but not the control drug dexmedetomidine, perturbed behavioral indices of predictions, their representation in higher-order cortex, feedback to posterior cortex, and pre-activation of sensory templates in higher-order sensory cortex. This study suggests that predictions depend on alpha activity in higher-order cortex, ß feedback, and NMDARs, and ketamine blocks access to learned predictive information.SIGNIFICANCE STATEMENT We learn the statistical regularities around us, creating associations between sensory stimuli. These associations can be exploited by generating predictions, which enable fast and efficient behavior. When predictions are perturbed, it can negatively influence perception and even contribute to psychiatric disorders, such as schizophrenia. Here we show that the frontal lobe generates predictions and sends them to posterior brain areas, to activate representations of predicted sensory stimuli before their appearance. Oscillations in neural activity (α and ß waves) are vital for these predictive mechanisms. The drug ketamine blocks predictions and the underlying mechanisms. This suggests that the generation of predictions in the frontal lobe, and the feedback pre-activating sensory representations in advance of stimuli, depend on NMDARs.

Convergent brain microstructure across multiple genetic models of schizophrenia and autism spectrum disorder: A feasibility study.

Neuroimaging studies of psychiatric illness have revealed a broad spectrum of structural and functional perturbations that have been attributed in part to the complex genetic heterogeneity underpinning these disorders. These perturbations have been identified in both preclinical genetic models and in patients when compared to control populations, but recent work has also demonstrated strong evidence for genetic, molecular, and structural convergence of several psychiatric diseases. We explored potential similarities in neural microstructure in preclinical genetic models of ASD (Fmr1, Nrxn1, Pten) and schizophrenia (Disc1 svΔ2) and in age- and sex-matched control animals with diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI). Our findings demonstrate a convergence in brain microstructure across these four genetic models with both tract-based and region-of-interest based analyses, which continues to buttress an emerging understanding of converging neural microstructure in psychiatric disease.

Postoperative delirium is associated with increased plasma neurofilament light.

While delirium is associated with cognitive decline and dementia, there is limited evidence to support causality for this relationship. Clarification of how delirium may cause cognitive decline, perhaps through evidence of contemporaneous neuronal injury, would enhance plausibility for a causal relationship. Dose-dependence of neuronal injury with delirium severity would further enhance the biological plausibility for this relationship. We tested whether delirium is associated with neuronal injury in 114 surgical patients recruited to a prospective biomarker cohort study. Patients underwent perioperative testing for changes in neurofilament light, a neuronal injury biomarker, as well as a panel of 10 cytokines, with contemporaneous assessment of delirium severity and incidence. A subset of patients underwent preoperative MRI. Initially we confirmed prior reports that neurofilament light levels correlated with markers of neurodegeneration [hippocampal volume (ΔR2 = 0.129, P = 0.015)] and white matter changes including fractional anisotropy of white matter (ΔR2 = 0.417, P < 0.001) with similar effects on mean, axial and radial diffusivity) in our cohort and that surgery was associated with increasing neurofilament light from preoperative levels [mean difference (95% confidence interval, CI) = 0.240 (0.178, 0.301) log10 (pg/ml), P < 0.001], suggesting putative neuronal injury. Next, we tested the relationship with delirium. Neurofilament light rose more sharply in participants with delirium compared to non-sufferers [mean difference (95% CI) = 0.251 (0.136, 0.367) log10 (pg/ml), P < 0.001]. This relationship showed dose-dependence, such that neurofilament light rose proportionately to delirium severity (ΔR2 = 0.199, P < 0.001). Given that inflammation is considered an important driver of postoperative delirium, next we tested whether neurofilament light, as a potential marker of neurotoxicity, may contribute to the pathogenesis of delirium independent of inflammation. From a panel of 10 cytokines, the pro-inflammatory cytokine IL-8 exhibited a strong correlation with delirium severity (ΔR2 = 0.208, P < 0.001). Therefore, we tested whether the change in neurofilament light contributed to delirium severity independent of IL-8. Neurofilament light was independently associated with delirium severity after adjusting for the change in inflammation (ΔR2 = 0.040, P = 0.038). These data suggest delirium is associated with exaggerated increases in neurofilament light and that this putative neurotoxicity may contribute to the pathogenesis of delirium itself, independent of changes in inflammation.

Human Gut Microbiota from Autism Spectrum Disorder Promote Behavioral Symptoms in Mice.

Autism spectrum disorder (ASD) manifests as alterations in complex human behaviors including social communication and stereotypies. In addition to genetic risks, the gut microbiome differs between typically developing (TD) and ASD individuals, though it remains unclear whether the microbiome contributes to symptoms. We transplanted gut microbiota from human donors with ASD or TD controls into germ-free mice and reveal that colonization with ASD microbiota is sufficient to induce hallmark autistic behaviors. The brains of mice colonized with ASD microbiota display alternative splicing of ASD-relevant genes. Microbiome and metabolome profiles of mice harboring human microbiota predict that specific bacterial taxa and their metabolites modulate ASD behaviors. Indeed, treatment of an ASD mouse model with candidate microbial metabolites improves behavioral abnormalities and modulates neuronal excitability in the brain. We propose that the gut microbiota regulates behaviors in mice via production of neuroactive metabolites, suggesting that gut-brain connections contribute to the pathophysiology of ASD.

The MPLEx Protocol for Multi-omic Analyses of Soil Samples.

Mass spectrometry (MS)-based integrated metaproteomic, metabolomic, and lipidomic (multi-omic) studies are transforming our ability to understand and characterize microbial communities in environmental and biological systems. These measurements are even enabling enhanced analyses of complex soil microbial communities, which are the most complex microbial systems known to date. Multi-omic analyses, however, do have sample preparation challenges, since separate extractions are typically needed for each omic study, thereby greatly amplifying the preparation time and amount of sample required. To address this limitation, a 3-in-1 method for the simultaneous extraction of metabolites, proteins, and lipids (MPLEx) from the same soil sample was created by adapting a solvent-based approach. This MPLEx protocol has proven to be both simple and robust for many sample types, even when utilized for limited quantities of complex soil samples. The MPLEx method also greatly enabled the rapid multi-omic measurements needed to gain a better understanding of the members of each microbial community, while evaluating the changes taking place upon biological and environmental perturbations.

MERS-CoV and H5N1 influenza virus antagonize antigen presentation by altering the epigenetic landscape.

Convergent evolution dictates that diverse groups of viruses will target both similar and distinct host pathways to manipulate the immune response and improve infection. In this study, we sought to leverage this uneven viral antagonism to identify critical host factors that govern disease outcome. Utilizing a systems-based approach, we examined differential regulation of IFN-γ-dependent genes following infection with robust respiratory viruses including influenza viruses [A/influenza/Vietnam/1203/2004 (H5N1-VN1203) and A/influenza/California/04/2009 (H1N1-CA04)] and coronaviruses [severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome CoV (MERS-CoV)]. Categorizing by function, we observed down-regulation of gene expression associated with antigen presentation following both H5N1-VN1203 and MERS-CoV infection. Further examination revealed global down-regulation of antigen-presentation gene expression, which was confirmed by proteomics for both H5N1-VN1203 and MERS-CoV infection. Importantly, epigenetic analysis suggested that DNA methylation, rather than histone modification, plays a crucial role in MERS-CoV-mediated antagonism of antigen-presentation gene expression; in contrast, H5N1-VN1203 likely utilizes a combination of epigenetic mechanisms to target antigen presentation. Together, the results indicate a common mechanism utilized by H5N1-VN1203 and MERS-CoV to modulate antigen presentation and the host adaptive immune response.

Multi-platform 'Omics Analysis of Human Ebola Virus Disease Pathogenesis.

The pathogenesis of human Ebola virus disease (EVD) is complex. EVD is characterized by high levels of virus replication and dissemination, dysregulated immune responses, extensive virus- and host-mediated tissue damage, and disordered coagulation. To clarify how host responses contribute to EVD pathophysiology, we performed multi-platform 'omics analysis of peripheral blood mononuclear cells and plasma from EVD patients. Our results indicate that EVD molecular signatures overlap with those of sepsis, imply that pancreatic enzymes contribute to tissue damage in fatal EVD, and suggest that Ebola virus infection may induce aberrant neutrophils whose activity could explain hallmarks of fatal EVD. Moreover, integrated biomarker prediction identified putative biomarkers from different data platforms that differentiated survivors and fatalities early after infection. This work reveals insight into EVD pathogenesis, suggests an effective approach for biomarker identification, and provides an important community resource for further analysis of human EVD severity.

Sexual dimorphism in the fetal cardiac response to maternal nutrient restriction.

Poor maternal nutrition causes intrauterine growth restriction (IUGR); however, its effects on fetal cardiac development are unclear. We have developed a baboon model of moderate maternal undernutrition, leading to IUGR. We hypothesized that the IUGR affects fetal cardiac structure and metabolism. Six control pregnant baboons ate ad-libitum (CTRL)) or 70% CTRL from 0.16 of gestation (G). Fetuses were euthanized at C-section at 0.9G under general anesthesia. Male but not female IUGR fetuses showed left ventricular fibrosis inversely correlated with birth weight. Expression of extracellular matrix protein TSP-1 was increased (p<0.05) in male IUGR. Expression of cardiac fibrotic markers TGFß, SMAD3 and ALK-1 were downregulated in male IUGRs with no difference in females. Autophagy was present in male IUGR evidenced by upregulation of ATG7 expression and lipidation LC3B. Global miRNA expression profiling revealed 56 annotated and novel cardiac miRNAs exclusively dysregulated in female IUGR, and 38 cardiac miRNAs were exclusively dysregulated in males (p<0.05). Fifteen (CTRL) and 23 (IUGR) miRNAs, were differentially expressed between males and females (p<0.05) suggesting sexual dimorphism, which can be at least partially explained by differential expression of upstream transcription factors (e.g. HNF4α, and NFκB p50). Lipidomics analysis of fetal cardiac tissue exhibited a net increase in diacylglycerol and plasmalogens and a decrease in triglycerides and phosphatidylcholines. In summary, IUGR resulting from decreased maternal nutrition is associated with sex-dependent dysregulations in cardiac structure, miRNA expression, and lipid metabolism. If these changes persist postnatally, they may program offspring for higher later life cardiac risk.

PIXiE: an algorithm for automated ion mobility arrival time extraction and collision cross section calculation using global data association.

MOTIVATION: Drift tube ion mobility spectrometry coupled with mass spectrometry (DTIMS-MS) is increasingly implemented in high throughput omics workflows, and new informatics approaches are necessary for processing the associated data. To automatically extract arrival times for molecules measured by DTIMS at multiple electric fields and compute their associated collisional cross sections (CCS), we created the PNNL Ion Mobility Cross Section Extractor (PIXiE). The primary application presented for this algorithm is the extraction of data that can then be used to create a reference library of experimental CCS values for use in high throughput omics analyses. RESULTS: We demonstrate the utility of this approach by automatically extracting arrival times and calculating the associated CCSs for a set of endogenous metabolites and xenobiotics. The PIXiE-generated CCS values were within error of those calculated using commercially available instrument vendor software. AVAILABILITY AND IMPLEMENTATION: PIXiE is an open-source tool, freely available on Github. The documentation, source code of the software, and a GUI can be found at https://github.com/PNNL-Comp-Mass-Spec/PIXiE and the source code of the backend workflow library used by PIXiE can be found at https://github.com/PNNL-Comp-Mass-Spec/IMS-Informed-Library . CONTACT: erin.baker@pnnl.gov or thomas.metz@pnnl.gov. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

LIQUID: an-open source software for identifying lipids in LC-MS/MS-based lipidomics data.

SUMMARY: We introduce an open-source software, LIQUID, for semi-automated processing and visualization of LC-MS/MS-based lipidomics data. LIQUID provides users with the capability to process high throughput data and contains a customizable target library and scoring model per project needs. The graphical user interface provides visualization of multiple lines of spectral evidence for each lipid identification, allowing rapid examination of data for making confident identifications of lipid molecular species. LIQUID was compared to other freely available software commonly used to identify lipids and other small molecules (e.g. CFM-ID, MetFrag, GNPS, LipidBlast and MS-DIAL), and was found to have a faster processing time to arrive at a higher number of validated lipid identifications. AVAILABILITY AND IMPLEMENTATION: LIQUID is available at http://github.com/PNNL-Comp-Mass-Spec/LIQUID . CONTACT: jennifer.kyle@pnnl.gov or thomas.metz@pnnl.gov. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MPLEx: a method for simultaneous pathogen inactivation and extraction of samples for multi-omics profiling.

The continued emergence and spread of infectious agents is of great concern, and systems biology approaches to infectious disease research can advance our understanding of host-pathogen relationships and facilitate the development of new therapies and vaccines. Molecular characterization of infectious samples outside of appropriate biosafety containment can take place only subsequent to pathogen inactivation. Herein, we describe a modified Folch extraction using chloroform/methanol that facilitates the molecular characterization of infectious samples by enabling simultaneous pathogen inactivation and extraction of proteins, metabolites, and lipids for subsequent mass spectrometry-based multi-omics measurements. This single-sample metabolite, protein and lipid extraction (MPLEx) method resulted in complete inactivation of clinically important bacterial and viral pathogens with exposed lipid membranes, including Yersinia pestis, Salmonella Typhimurium, and Campylobacter jejuni in pure culture, and Yersinia pestis, Campylobacter jejuni, and West Nile, MERS-CoV, Ebola, and influenza H7N9 viruses in infection studies. In addition, >99% inactivation, which increased with solvent exposure time, was also observed for pathogens without exposed lipid membranes including community-associated methicillin-resistant Staphylococcus aureus, Clostridium difficile spores and vegetative cells, and adenovirus type 5. The overall pipeline of inactivation and subsequent proteomic, metabolomic, and lipidomic analyses was evaluated using a human epithelial lung cell line infected with wild-type and mutant influenza H7N9 viruses, thereby demonstrating that MPLEx yields biomaterial of sufficient quality for subsequent multi-omics analyses. Based on these experimental results, we believe that MPLEx will facilitate systems biology studies of infectious samples by enabling simultaneous pathogen inactivation and multi-omics measurements from a single specimen with high success for pathogens with exposed lipid membranes.

Comparing identified and statistically significant lipids and polar metabolites in 15-year old serum and dried blood spot samples for longitudinal studies.

RATIONALE: The use of dried blood spots (DBS) has many advantages over traditional plasma and serum samples such as the smaller blood volume required, storage at room temperature, and ability to sample in remote locations. However, understanding the robustness of different analytes in DBS samples is essential, especially in older samples collected for longitudinal studies. METHODS: Here we analyzed the stability of polar metabolites and lipids in DBS samples collected in 2000-2001 and stored at room temperature. The identified and statistically significant molecules were then compared to matched serum samples stored at -80°C to determine if the DBS samples could be effectively used in a longitudinal study following metabolic disease. RESULTS: A total of 400 polar metabolites and lipids were identified in the serum and DBS samples using gas chromatograph/mass spectrometry (GC/MS), liquid chromatography (LC)/MS, and LC/ion mobility spectrometry-MS (LC/IMS-MS). The identified polar metabolites overlapped well between the sample types, though only one statistically significant metabolite was conserved in a case-control study of older diabetic males with low amounts of high-density lipoproteins and high body mass indices, triacylglycerides and glucose levels when compared to non-diabetic patients with normal levels, indicating that degradation in the DBS samples affects polar metabolite quantitation. Differences in the lipid identifications indicated that some oxidation occurs in the DBS samples. However, 36 statistically significant lipids correlated in both sample types. CONCLUSIONS: The difference in the number of statistically significant polar metabolites and lipids indicated that the lipids did not degrade to as great of a degree as the polar metabolites in the DBS samples and lipid quantitation was still possible. Copyright © 2016 John Wiley & Sons, Ltd.

Influence of early life exposure, host genetics and diet on the mouse gut microbiome and metabolome.

Although the gut microbiome plays important roles in host physiology, health and disease1, we lack understanding of the complex interplay between host genetics and early life environment on the microbial and metabolic composition of the gut. We used the genetically diverse Collaborative Cross mouse system2 to discover that early life history impacts the microbiome composition, whereas dietary changes have only a moderate effect. By contrast, the gut metabolome was shaped mostly by diet, with specific non-dietary metabolites explained by microbial metabolism. Quantitative trait analysis identified mouse genetic trait loci (QTL) that impact the abundances of specific microbes. Human orthologues of genes in the mouse QTL are implicated in gastrointestinal cancer. Additionally, genes located in mouse QTL for Lactobacillales abundance are implicated in arthritis, rheumatic disease and diabetes. Furthermore, Lactobacillales abundance was predictive of higher host T-helper cell counts, suggesting an important link between Lactobacillales and host adaptive immunity.

Simultaneous Proteomic Discovery and Targeted Monitoring using Liquid Chromatography, Ion Mobility Spectrometry, and Mass Spectrometry.

Current proteomic approaches include both broad discovery measurements and quantitative targeted analyses. In many cases, discovery measurements are initially used to identify potentially important proteins (e.g. candidate biomarkers) and then targeted studies are employed to quantify a limited number of selected proteins. Both approaches, however, suffer from limitations. Discovery measurements aim to sample the whole proteome but have lower sensitivity, accuracy, and quantitation precision than targeted approaches, whereas targeted measurements are significantly more sensitive but only sample a limited portion of the proteome. Herein, we describe a new approach that performs both discovery and targeted monitoring (DTM) in a single analysis by combining liquid chromatography, ion mobility spectrometry and mass spectrometry (LC-IMS-MS). In DTM, heavy labeled target peptides are spiked into tryptic digests and both the labeled and unlabeled peptides are detected using LC-IMS-MS instrumentation. Compared with the broad LC-MS discovery measurements, DTM yields greater peptide/protein coverage and detects lower abundance species. DTM also achieved detection limits similar to selected reaction monitoring (SRM) indicating its potential for combined high quality discovery and targeted analyses, which is a significant step toward the convergence of discovery and targeted approaches.

SNaPP: Simplified Nanoproteomics Platform for Reproducible Global Proteomic Analysis of Nanogram Protein Quantities.

Global proteomic analyses of complex protein samples in nanogram quantities require a fastidious approach to achieve in-depth protein coverage and quantitative reproducibility. Biological samples are often severely mass limited and can preclude the application of more robust bulk sample processing workflows. In this study, we present a system that minimizes sample handling by using online immobilized trypsin digestion and solid phase extraction to create a simple, sensitive, robust, and reproducible platform for the analysis of nanogram-size proteomic samples. To demonstrate the effectiveness of our simplified nanoproteomics platform, we used the system to analyze preimplantation blastocysts collected on day 4 of pregnancy by flushing the uterine horns with saline. For each of our three sample groups, blastocysts were pooled from three mice resulting in 22, 22, and 25 blastocysts, respectively. The resulting proteomic data provide novel insight into mouse blastocyst protein expression on day 4 of normal pregnancy because we characterized 348 proteins that were identified in at least two sample groups, including 59 enzymes and blastocyst specific proteins (eg, zona pellucida proteins). This technology represents an important advance in which future studies could perform global proteomic analyses of blastocysts obtained from an individual mouse, thereby enabling researchers to investigate interindividual variation as well as increase the statistical power without increasing animal numbers. This approach is also easily adaptable to other mass-limited sample types.