Wenzhong Xiao

Genomic responses in mouse models poorly mimic human inflammatory diseases

A cornerstone of modern biomedical research is the use of mouse models to explore basic pathophysiological mechanisms, evaluate new therapeutic approaches, and make go or no-go decisions to carry new drug candidates forward into clinical trials. Systematic studies evaluating how well murine models mimic human inflammatory diseases are nonexistent. Here, we show that, although acute inflammatory stresses from different etiologies result in highly similar genomic responses in humans, the responses in corresponding mouse models correlate poorly with the human conditions and also, one another. Among genes changed significantly in humans, the murine orthologs are close to random in matching their human counterparts (e.g., R2 between 0.0 and 0.1). In addition to improvements in the current animal model systems, our study supports higher priority for translational medical research to focus on the more complex human conditions rather than relying on mouse models to study human inflammatory diseases.

A network-based analysis of systemic inflammation in humans

Oligonucleotide and complementary DNA microarrays are being used to subclassify histologically similar tumours, monitor disease progress, and individualize treatment regimens. However, extracting new biological insight from high-throughput genomic studies of human diseases is a challenge, limited by difficulties in recognizing and evaluating relevant biological processes from huge quantities of experimental data. Here we present a structured network knowledge-base approach to analyse genome-wide transcriptional responses in the context of known functional interrelationships among proteins, small molecules and phenotypes. This approach was used to analyse changes in blood leukocyte gene expression patterns in human subjects receiving an inflammatory stimulus (bacterial endotoxin). We explore the known genome-wide interaction network to identify significant functional modules perturbed in response to this stimulus. Our analysis reveals that the human blood leukocyte response to acute systemic inflammation includes the transient dysregulation of leukocyte bioenergetics and modulation of translational machinery. These findings provide insight into the regulation of global leukocyte activities as they relate to innate immune system tolerance and increased susceptibility to infection in humans.

A genomic storm in critically injured humans

Critical injury in humans induces a genomic storm with simultaneous changes in expression of innate and adaptive immunity genes.

Isolating highly enriched populations of circulating epithelial cells and other rare cells from blood using a magnetic sweeper device

The enumeration of rare circulating epithelial cells (CEpCs) in the peripheral blood of metastatic cancer patients has shown promise for improved cancer prognosis. Moving beyond enumeration, molecular analysis of CEpCs may provide candidate surrogate endpoints to diagnose, treat, and monitor malignancy directly from the blood samples. Thorough molecular analysis of CEpCs requires the development of new sample preparation methods that yield easily accessible and purified CEpCs for downstream biochemical assays. Here, we describe a new immunomagnetic cell separator, the MagSweeper, which gently enriches target cells and eliminates cells that are not bound to magnetic particles. The isolated cells are easily accessible and can be extracted individually based on their physical characteristics to deplete any cells nonspecifically bound to beads. We have shown that our device can process 9 mL of blood per hour and captures >50% of CEpCs as measured in spiking experiments. We have shown that the separation process does not perturb the gene expression of rare cells. To determine the efficiency of our platform in isolating CEpCs from patients, we have isolated CEpCs from all 47 tubes of 9-mL blood samples collected from 17 women with metastatic breast cancer. In contrast, we could not find any circulating epithelial cells in samples from 5 healthy donors. The isolated CEpCs are all stored individually for further molecular analysis.

A Transcriptional Profile of Aging in the Human Kidney

In this study, we found 985 genes that change expression in the cortex and the medulla of the kidney with age. Some of the genes whose transcripts increase in abundance with age are known to be specifically expressed in immune cells, suggesting that immune surveillance or inflammation increases with age. The age-regulated genes show a similar aging profile in the cortex and the medulla, suggesting a common underlying mechanism for aging. Expression profiles of these age-regulated genes mark not only age, but also the relative health and physiology of the kidney in older individuals. Finally, the set of aging-regulated kidney genes suggests specific mechanisms and pathways that may play a role in kidney degeneration with age.

Integrative Analysis of the Mitochondrial Proteome in Yeast

In this study yeast mitochondria were used as a model system to apply, evaluate, and integrate different genomic approaches to define the proteins of an organelle. Liquid chromatography mass spectrometry applied to purified mitochondria identified 546 proteins. By expression analysis and comparison to other proteome studies, we demonstrate that the proteomic approach identifies primarily highly abundant proteins. By expanding our evaluation to other types of genomic approaches, including systematic deletion phenotype screening, expression profiling, subcellular localization studies, protein interaction analyses, and computational predictions, we show that an integration of approaches moves beyond the limitations of any single approach. We report the success of each approach by benchmarking it against a reference set of known mitochondrial proteins, and predict approximately 700 proteins associated with the mitochondrial organelle from the integration of 22 datasets. We show that a combination of complementary approaches like deletion phenotype screening and mass spectrometry can identify over 75% of the known mitochondrial proteome. These findings have implications for choosing optimal genome-wide approaches for the study of other cellular systems, including organelles and pathways in various species. Furthermore, our systematic identification of genes involved in mitochondrial function and biogenesis in yeast expands the candidate genes available for mapping Mendelian and complex mitochondrial disorders in humans.

Quantitative proteome analysis of human plasma following in vivo lypopolysaccharide administration using 16O/18O labeling and the accurate mass and time tag approach

Identification of novel diagnostic or therapeutic biomarkers from human blood plasma would benefit significantly from quantitative measurements of the proteome constituents over a range of physiological conditions. Herein we describe an initial demonstration of proteome-wide quantitative analysis of human plasma. The approach utilizes postdigestion trypsin-catalyzed 16O/18O peptide labeling, two-dimensional LC-FTICR mass spectrometry, and the accurate mass and time (AMT) tag strategy to identify and quantify peptides/proteins from complex samples. A peptide accurate mass and LC elution time AMT tag data base was initially generated using MS/MS following extensive multidimensional LC separations to provide the basis for subsequent peptide identifications. The AMT tag data base contains >8,000 putative identified peptides, providing 938 confident plasma protein identifications. The quantitative approach was applied without depletion of high abundance proteins for comparative analyses of plasma samples from an individual prior to and 9 h after lipopolysaccharide (LPS) administration. Accurate quantification of changes in protein abundance was demonstrated by both 1:1 labeling of control plasma and the comparison between the plasma samples following LPS administration. A total of 429 distinct plasma proteins were quantified from the comparative analyses, and the protein abundances for 25 proteins, including several known inflammatory response mediators, were observed to change significantly following LPS administration.

The Drosophila melanogaster Toll Pathway Participates in Resistance to Infection by the Gram-Negative Human Pathogen Pseudomonas aeruginosa

ABSTRACT Pseudomonas aeruginosa is a gram-negative pathogen that infects immunocompromised and cystic fibrosis patients. The molecular basis of the host-P. aeruginosa interaction and the effect of specific P. aeruginosa virulence factors on various components of the innate immunity pathways are largely unknown. We examine interactions between P. aeruginosa virulence factors and components of innate immunity response in the Drosophila melanogaster model system to reveal the importance of the Toll signaling pathway in resistance to infection by the P. aeruginosa human isolate PA14. Using the two PA14-isogenic mutants plcS and dsbA, we show that Drosophila loss-of-function mutants of Spatzle, the extracellular ligand of Toll, and Dorsal and Dif, two NF-κB-like transcription factors, allow increased P. aeruginosa infectivity within fly tissues. In contrast, a constitutively active Toll mutant and a loss-of-function mutant of Cactus, an IκB-like factor that inhibits the Toll signaling, reduce infectivity. Our finding that Dorsal activity is required to restrict P. aeruginosa infectivity in Drosophila provides direct in vivo evidence for Dorsal function in adult fly immunity. Additionally, our results provide the basis for future studies into interactions between P. aeruginosa virulence factors and components of the Toll signaling pathway, which is functionally conserved between flies and humans.

High Dynamic Range Characterization of the Trauma Patient Plasma Proteome

Although human plasma represents an attractive sample for disease biomarker discovery, the extreme complexity and large dynamic range in protein concentrations present significant challenges for characterization, candidate biomarker discovery, and validation. Herein we describe a strategy that combines immunoaffinity subtraction and subsequent chemical fractionation based on cysteinyl peptide and N-glycopeptide captures with two-dimensional LC-MS/MS to increase the dynamic range of analysis for plasma. Application of this “divide-and-conquer” strategy to trauma patient plasma significantly improved the overall dynamic range of detection and resulted in confident identification of 22,267 unique peptides from four different peptide populations (cysteinyl peptides, non-cysteinyl peptides, N-glycopeptides, and non-glycopeptides) that covered 3654 different proteins with 1494 proteins identified by multiple peptides. Numerous low abundance proteins were identified, exemplified by 78 “classic” cytokines and cytokine receptors and by 136 human cell differentiation molecules. Additionally a total of 2910 different N-glycopeptides that correspond to 662 N-glycoproteins and 1553 N-glycosylation sites were identified. A panel of the proteins identified in this study is known to be involved in inflammation and immune responses. This study established an extensive reference protein database for trauma patients that provides a foundation for future high throughput quantitative plasma proteomic studies designed to elucidate the mechanisms that underlie systemic inflammatory responses.

High-throughput VDJ sequencing for quantification of minimal residual disease in chronic lymphocytic leukemia and immune reconstitution assessment

The primary cause of poor outcome following allogeneic hematopoietic cell transplantation (HCT) for chronic lymphocytic leukemia (CLL) is disease recurrence. Detection of increasing minimal residual disease (MRD) following HCT may permit early intervention to prevent clinical relapse; however, MRD quantification remains an uncommon diagnostic test because of logistical and financial barriers to widespread use. Here we describe a method for quantifying CLL MRD using widely available consensus primers for amplification of all Ig heavy chain (IGH) genes in a mixture of peripheral blood mononuclear cells, followed by high-throughput sequencing (HTS) for disease-specific IGH sequence quantification. To achieve accurate MRD quantification, we developed a systematic bioinformatic methodology to aggregate cancer clone sequence variants arising from systematic and random artifacts occurring during IGH-HTS. We then compared the sensitivity of IGH-HTS, flow cytometry, and allele-specific oligonucleotide PCR for MRD quantification in 28 samples collected from 6 CLL patients following allogeneic HCT. Using amplimer libraries generated with consensus primers from patient blood samples, we demonstrate the sensitivity of IGH-HTS with 454 pyrosequencing to be 10−5, with a high correlation between quantification by allele-specific oligonucleotide PCR and IGH-HTS (r = 0.85). From the same dataset used to quantify MRD, IGH-HTS also allowed us to profile IGH repertoire reconstitution after HCT—information not provided by the other MRD methods. IGH-HTS using consensus primers will broaden the availability of MRD quantification in CLL and other B cell malignancies, and this approach has potential for quantitative evaluation of immune diversification following transplant and nontransplant therapies.