SARS-CoV-2 vaccination in the first year after hematopoietic cell transplant or chimeric antigen receptor T cell therapy: A prospective, multicenter, observational study (BMT CTN 2101).

Background: The optimal timing of vaccination with SARS-CoV-2 vaccines after cellular therapy is incompletely understood. Objective: To describe humoral and cellular responses after SARS-CoV-2 vaccination initiated <4 months versus 4-12 months after cellular therapy. Design: Multicenter prospective observational study. Setting: 34 centers in the United States. Participants: 466 allogeneic hematopoietic cell transplant (HCT; n=231), autologous HCT (n=170), or chimeric antigen receptor T cell (CAR-T cell) therapy (n=65) recipients enrolled between April 2021 and June 2022. Interventions: SARS-CoV-2 vaccination as part of routine care. Measurements: We obtained blood prior to and after vaccinations at up to five time points and tested for SARS-CoV-2 spike (anti-S) IgG in all participants and neutralizing antibodies for Wuhan D614G, Delta B.1.617.2, and Omicron B.1.1.529 strains, as well as SARS-CoV-2-specific T cell receptors (TCRs), in a subgroup. Results: Anti-S IgG and neutralizing antibody responses increased with vaccination in HCT recipients irrespective of vaccine initiation timing but were unchanged in CAR-T cell recipients initiating vaccines within 4 months. Anti-S IgG ≥2,500 U/mL was correlated with high neutralizing antibody titers and attained by the last time point in 70%, 69%, and 34% of allogeneic HCT, autologous HCT, and CAR-T cell recipients, respectively. SARS-CoV-2-specific T cell responses were attained in 57%, 83%, and 58%, respectively. Humoral and cellular responses did not significantly differ among participants initiating vaccinations <4 months vs 4-12 months after cellular therapy. Pre-cellular therapy SARS-CoV-2 infection or vaccination were key predictors of post-cellular therapy anti-S IgG levels. Limitations: The majority of participants were adults and received mRNA vaccines. Conclusions: These data support starting mRNA SARS-CoV-2 vaccination three to four months after allogeneic HCT, autologous HCT, and CAR-T cell therapy. Funding: National Marrow Donor Program, Leukemia and Lymphoma Society, Multiple Myeloma Research Foundation, Novartis, LabCorp, American Society for Transplantation and Cellular Therapy, Adaptive Biotechnologies, and the National Institutes of Health.

Impact of COVID-19 vaccination on symptoms and immune phenotypes in vaccine-naïve individuals with Long COVID.

Background: Long COVID contributes to the global burden of disease. Proposed root cause hypotheses include the persistence of SARS-CoV-2 viral reservoir, autoimmunity, and reactivation of latent herpesviruses. Patients have reported various changes in Long COVID symptoms after COVID-19 vaccinations, leaving uncertainty about whether vaccine-induced immune responses may alleviate or worsen disease pathology. Methods: In this prospective study, we evaluated changes in symptoms and immune responses after COVID-19 vaccination in 16 vaccine-naïve individuals with Long COVID. Surveys were administered before vaccination and then at 2, 6, and 12 weeks after receiving the first vaccine dose of the primary series. Simultaneously, SARS-CoV-2-reactive TCR enrichment, SARS-CoV-2-specific antibody responses, antibody responses to other viral and self-antigens, and circulating cytokines were quantified before vaccination and at 6 and 12 weeks after vaccination. Results: Self-report at 12 weeks post-vaccination indicated 10 out of 16 participants had improved health, 3 had no change, 1 had worse health, and 2 reported marginal changes. Significant elevation in SARS-CoV-2-specific TCRs and Spike protein-specific IgG were observed 6 and 12 weeks after vaccination. No changes in reactivities were observed against herpes viruses and self-antigens. Within this dataset, higher baseline sIL-6R was associated with symptom improvement, and the two top features associated with non-improvement were high IFN-ß and CNTF, among soluble analytes. Conclusions: Our study showed that in this small sample, vaccination improved the health or resulted in no change to the health of most participants, though few experienced worsening. Vaccination was associated with increased SARS-CoV-2 Spike protein-specific IgG and T cell expansion in most individuals with Long COVID. Symptom improvement was observed in those with baseline elevated sIL-6R, while elevated interferon and neuropeptide levels were associated with a lack of improvement.

SARS-CoV-2 vaccination in the first year after allogeneic hematopoietic cell transplant: a prospective, multicentre, observational study.

Background: The optimal timing for SARS-CoV-2 vaccines within the first year after allogeneic hematopoietic cell transplant (HCT) is poorly understood. Methods: We conducted a prospective, multicentre, observational study of allogeneic HCT recipients who initiated SARS-CoV-2 vaccinations within 12 months of HCT. Participants were enrolled at 22 academic cancer centers across the United States. Participants of any age who were planning to receive a first post-HCT SARS-CoV-2 vaccine within 12 months of HCT were eligible. We obtained blood prior to and after each vaccine dose for up to four vaccine doses, with an end-of-study sample seven to nine months after enrollment. We tested for SARS-CoV-2 spike protein (anti-S) IgG; nucleocapsid protein (anti-N) IgG; neutralizing antibodies for Wuhan D614G, Delta B.1.617.2, and Omicron B.1.1.529 strains; and SARS-CoV-2-specific T-cell receptors (TCRs). The primary outcome was a comparison of anti-S IgG titers at the post-V2 time point in participants initiating vaccinations <4 months versus 4-12 months after HCT using a propensity-adjusted analysis. We also evaluated factors associated with high-level anti-S IgG titers (≥2403 U/mL) in logistic regression models. Findings: Between April 22, 2021 and November 17, 2021, 175 allogeneic HCT recipients were enrolled in the study, of whom all but one received mRNA SARS-CoV-2 vaccines. SARS-CoV-2 anti-S IgG titers, neutralizing antibody titers, and TCR breadth and depth did not significantly differ at all tested time points following the second vaccination among those initiating vaccinations <4 months versus 4-12 months after HCT. Anti-S IgG ≥2403 U/mL correlated with neutralizing antibody levels similar to those observed in a prior study of non-immunocompromised individuals, and 57% of participants achieved anti-S IgG ≥2403 U/mL at the end-of-study time point. In models adjusted for SARS-CoV-2 infection pre-enrollment, SARS-CoV-2 vaccination pre-HCT, CD19+ B-cell count, CD4+ T-cell count, and age (as applicable to the model), vaccine initiation timing was not associated with high-level anti-S IgG titers at the post-V2, post-V3, or end-of-study time points. Notably, prior graft-versus-host-disease (GVHD) or use of immunosuppressive medications were not associated with high-level anti-S IgG titers. Grade ≥3 vaccine-associated adverse events were infrequent. Interpretation: These data support starting mRNA SARS-CoV-2 vaccination three months after HCT, irrespective of concurrent GVHD or use of immunosuppressive medications. This is one of the largest prospective analyses of vaccination for any pathogen within the first year after allogeneic HCT and supports current guidelines for SARS-CoV-2 vaccination starting three months post-HCT. Additionally, there are few studies of mRNA vaccine formulations for other pathogens in HCT recipients, and these data provide encouraging proof-of-concept for the utility of early vaccination targeting additional pathogens with mRNA vaccine platforms. Funding: National Marrow Donor Program, Leukemia and Lymphoma Society, Multiple Myeloma Research Foundation, Novartis, LabCorp, American Society for Transplantation and Cellular Therapy, Adaptive Biotechnologies, and the National Institutes of Health.

Characterisation of T cell receptor repertoires in coeliac disease.

AIMS: Characterise T-cell receptor gene (TR) repertoires of small intestinal T cells of patients with newly diagnosed (active) coeliac disease (ACD), refractory CD type I (RCD I) and patients with CD on a gluten-free diet (GFD). METHODS: Next-generation sequencing of complementarity-determining region 3 (CDR3) of rearranged T cell receptor ß (TRB) and γ (TRG) genes was performed using DNA extracted from intraepithelial cell (IEC) and lamina propria cell (LPC) fractions and a small subset of peripheral blood mononuclear cell (PBMC) samples obtained from CD and non-CD (control) patients. Several parameters were assessed, including relative abundance and enrichment. RESULTS: TRB and TRG repertoires of CD IEC and LPC samples demonstrated lower clonality but higher frequency of rearranged TRs compared with controls. No CD-related differences were detected in the limited number of PBMC samples. Previously published LP gliadin-specific TRB sequences were more frequently detected in LPC samples from patients with CD compared with non-CD controls. TRG repertoires of IECs from both ACD and GFD patients demonstrated increased abundance of certain CDR3 amino acid (AA) motifs compared with controls, which were encoded by multiple nucleotide variants, including one motif that was enriched in duodenal IECs versus the PBMCs of CD patients. CONCLUSIONS: Small intestinal TRB and TRG repertoires of patients with CD are more diverse than individuals without CD, likely due to mucosal recruitment and accumulation of T cells because of protracted inflammation. Enrichment of the unique TRG CDR3 AA sequence in the mucosa of patients with CD may suggest disease-associated changes in the TCRγδ IE lymphocyte (IEL) landscape.

Humoral and Cellular Immune Response to Covid-19 Vaccination in Patients with Chronic Graft-versus-Host Disease on Immunosuppression.

Chronic graft-versus-host disease (cGVHD) and its management with immunosuppressive therapies increase the susceptibility to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, as well as progression to severe Coronavirus 19 disease (COVID-19). Vaccination against COVID-19 is strongly recommended, but efficacy data are limited in this patient population. In this study, responses to COVID-19 vaccination were measured at 3 time points-after the initial vaccine series, before the third dose, and after the third dose-in adults with cGVHD receiving immunosuppressive therapy. Humoral response was measured by quantitative anti-spike antibody and neutralizing antibody levels. Anti-nucleocapsid antibody levels were measured to detect natural infection. T cell response was evaluated by a novel immunosequencing technique combined with immune repertoire profiling from cryopreserved peripheral blood mononuclear cell samples. Present or absent T cell responses were determined by the relative proportion of unique SARS-CoV-2-associated T cell receptor sequences ("breadth") plus clonal expansion of the response ("depth") compared with those in a reference population. Based on both neutralizing antibody and T cell responses, patients were categorized as vaccine responders (both detected), nonresponders (neither detected), or mixed (one but not both detected). Thirty-two patients were enrolled for the initial series, including 17 (53%) positive responders, 7 (22%) mixed responders, and 8 (25%) nonresponders. All but one patient categorized as mixed responders had humoral responses while lacking T cell responses. No statistical differences were observed in patient characteristics among the 3 groups of patients categorized by immune response, although sample sizes were limited. Significant positive correlations were observed between the robustness of cellular and humoral responses after the initial series. Among the 20 patients with paired samples (pre- and post-third dose), a third vaccination resulted in increased neutralizing antibody titers. cGVHD worsened in 10 patients (26%; 6 after the initial series and 4 after the third dose), necessitating escalation of immunosuppressive doses in 5 patients, although 4 had been tapering immunosuppression and 5 had already worsening cGVHD at the time of vaccination, and a clear association between COVID-19 vaccination and cGVHD could not be drawn. Among the patients with cGVHD on immunosuppressive therapy, 72% demonstrated a neutralizing antibody response after a 2-dose primary COVID-19 vaccination, two-thirds of whom also developed a T cell response; 25% had neither a humoral nor a T cell response. A third dose further amplified the antibody response.

Assessment of Clonotypic Rearrangements and Minimal Residual Disease in Lymphoid Malignancies.

CONTEXT.­: Measurable (minimal) residual disease (MRD) is an independent prognostic factor for survival outcomes in patients with lymphoid and plasma cell malignancies and has been incorporated into consensus criteria regarding treatment response, strategy, and clinical trial endpoints. clonoSEQ (a next-generation sequencing [NGS]-MRD assay) uses multiplex polymerase chain reaction and NGS to identify clonotypic rearrangements at the immunoglobulin (Ig) H, IgK, IgL, T-cell receptor (TCR)-ß, and TCR-γ loci, as well as translocated B-cell lymphoma 1/IgH and 2/IgH sequences for MRD assessment. Additionally, it can be used to confirm diagnoses of cutaneous T-cell lymphoma (CTCL). OBJECTIVE.­: To review the technical aspects of our experience using the clonoSEQ Assay in routine clinical practice. DESIGN.­: In this single-center experience, 390 patients with lymphoid and plasma cell malignancies were assessed with the NGS-MRD Assay at a central laboratory. RESULTS.­: Median time from arrival of the shipment to initiation of the assay (defined as captured in Adaptive's secure tracking system) was 2.1 hours. Overall, 317 patients had 1 or more samples submitted for sequence identification. Of these, 290 (91.5%) had trackable sequences identified. The median calibration rate of samples by malignancy (where n ≥ 10 samples, excluding CTCL samples) was 88.1%, across a variety of fresh and archived sample sources (177 of 201 samples). TCR-ß and/or TCR-γ clonotypes were identified in 40 of 95 samples (42.1%) from 66 patients with suspected CTCL. CONCLUSIONS.­: This NGS-MRD Assay is a valuable and sensitive tool for monitoring MRD in patients with plasma cell and lymphoid malignancies and assisting in the diagnosis of CTCL.

Monitoring of Circulating Tumor DNA Improves Early Relapse Detection After Axicabtagene Ciloleucel Infusion in Large B-Cell Lymphoma: Results of a Prospective Multi-Institutional Trial.

PURPOSE: Although the majority of patients with relapsed or refractory large B-cell lymphoma respond to axicabtagene ciloleucel (axi-cel), only a minority of patients have durable remissions. This prospective multicenter study explored the prognostic value of circulating tumor DNA (ctDNA) before and after standard-of-care axi-cel for predicting patient outcomes. METHODS: Lymphoma-specific variable, diversity, and joining gene segments (VDJ) clonotype ctDNA sequences were frequently monitored via next-generation sequencing from the time of starting lymphodepleting chemotherapy until progression or 1 year after axi-cel infusion. We assessed the prognostic value of ctDNA to predict outcomes and axi-cel-related toxicity. RESULTS: A tumor clonotype was successfully detected in 69 of 72 (96%) enrolled patients. Higher pretreatment ctDNA concentrations were associated with progression after axi-cel infusion and developing cytokine release syndrome and/or immune effector cell-associated neurotoxicity syndrome. Twenty-three of 33 (70%) durably responding patients versus 4 of 31 (13%) progressing patients demonstrated nondetectable ctDNA 1 week after axi-cel infusion (P < .0001). At day 28, patients with detectable ctDNA compared with those with undetectable ctDNA had a median progression-free survival and OS of 3 months versus not reached (P < .0001) and 19 months versus not reached (P = .0080), respectively. In patients with a radiographic partial response or stable disease on day 28, 1 of 10 patients with concurrently undetectable ctDNA relapsed; by contrast, 15 of 17 patients with concurrently detectable ctDNA relapsed (P = .0001). ctDNA was detected at or before radiographic relapse in 29 of 30 (94%) patients. All durably responding patients had undetectable ctDNA at or before 3 months after axi-cel infusion. CONCLUSION: Noninvasive ctDNA assessments can risk stratify and predict outcomes of patients undergoing axi-cel for the treatment of large B-cell lymphoma. These results provide a rationale for designing ctDNA-based risk-adaptive chimeric antigen receptor T-cell clinical trials.

Identification of a Blood-Based Protein Biomarker Panel for Lung Cancer Detection.

Lung cancer is the deadliest cancer worldwide, mainly due to its advanced stage at the time of diagnosis. A non-invasive method for its early detection remains mandatory to improve patients' survival. Plasma levels of 351 proteins were quantified by Liquid Chromatography-Parallel Reaction Monitoring (LC-PRM)-based mass spectrometry in 128 lung cancer patients and 93 healthy donors. Bootstrap sampling and least absolute shrinkage and selection operator (LASSO) penalization were used to find the best protein combination for outcome prediction. The PanelomiX platform was used to select the optimal biomarker thresholds. The panel was validated in 48 patients and 49 healthy volunteers. A 6-protein panel clearly distinguished lung cancer from healthy individuals. The panel displayed excellent performance: area under the receiver operating characteristic curve (AUC) = 0.999, positive predictive value (PPV) = 0.992, negative predictive value (NPV) = 0.989, specificity = 0.989 and sensitivity = 0.992. The panel detected lung cancer independently of the disease stage. The 6-protein panel and other sub-combinations displayed excellent results in the validation dataset. In conclusion, we identified a blood-based 6-protein panel as a diagnostic tool in lung cancer. Used as a routine test for high- and average-risk individuals, it may complement currently adopted techniques in lung cancer screening.

An integrated quantification method to increase the precision, robustness, and resolution of protein measurement in human plasma samples.

BACKGROUND: Current quantification methods for mass spectrometry (MS)-based proteomics either do not provide sufficient control of variability or are difficult to implement for routine clinical testing. RESULTS: We present here an integrated quantification (InteQuan) method that better controls pre-analytical and analytical variability than the popular quantification method using stable isotope-labeled standard peptides (SISQuan). We quantified 16 lung cancer biomarker candidates in human plasma samples in three assessment studies, using immunoaffinity depletion coupled with multiple reaction monitoring (MRM) MS. InteQuan outperformed SISQuan in precision in all three studies and tolerated a two-fold difference in sample loading. The three studies lasted over six months and encountered major changes in experimental settings. Nevertheless, plasma proteins in low ng/ml to low µg/ml concentrations were measured with a median technical coefficient of variation (CV) of 11.9% using InteQuan. The corresponding median CV using SISQuan was 15.3% after linear fitting. Furthermore, InteQuan surpassed SISQuan in measuring biological difference among clinical samples and in distinguishing benign versus cancer plasma samples. CONCLUSIONS: We demonstrated that InteQuan is a simple yet robust quantification method for MS-based quantitative proteomics, especially for applications in biomarker research and in routine clinical testing.

A blood-based proteomic classifier for the molecular characterization of pulmonary nodules.

Each year, millions of pulmonary nodules are discovered by computed tomography and subsequently biopsied. Because most of these nodules are benign, many patients undergo unnecessary and costly invasive procedures. We present a 13-protein blood-based classifier that differentiates malignant and benign nodules with high confidence, thereby providing a diagnostic tool to avoid invasive biopsy on benign nodules. Using a systems biology strategy, we identified 371 protein candidates and developed a multiple reaction monitoring (MRM) assay for each. The MRM assays were applied in a three-site discovery study (n = 143) on plasma samples from patients with benign and stage IA lung cancer matched for nodule size, age, gender, and clinical site, producing a 13-protein classifier. The classifier was validated on an independent set of plasma samples (n = 104), exhibiting a negative predictive value (NPV) of 90%. Validation performance on samples from a nondiscovery clinical site showed an NPV of 94%, indicating the general effectiveness of the classifier. A pathway analysis demonstrated that the classifier proteins are likely modulated by a few transcription regulators (NF2L2, AHR, MYC, and FOS) that are associated with lung cancer, lung inflammation, and oxidative stress networks. The classifier score was independent of patient nodule size, smoking history, and age, which are risk factors used for clinical management of pulmonary nodules. Thus, this molecular test provides a potential complementary tool to help physicians in lung cancer diagnosis.

Complexity of the microRNA repertoire revealed by next-generation sequencing.

MicroRNAs (miRNAs) have been implicated to play key roles in normal physiological functions, and altered expression of specific miRNAs has been associated with a number of diseases. It is of great interest to understand their roles and a prerequisite for such study is the ability to comprehensively and accurately assess the levels of the entire repertoire of miRNAs in a given sample. It has been shown that some miRNAs frequently have sequence variations termed isomirs. To better understand the extent of miRNA sequence heterogeneity and its potential implications for miRNA function and measurement, we conducted a comprehensive survey of miRNA sequence variations from human and mouse samples using next generation sequencing platforms. Our results suggest that the process of generating this isomir spectrum might not be random and that heterogeneity at the ends of miRNA affects the consistency and accuracy of miRNA level measurement. In addition, we have constructed a database from our sequencing data that catalogs the entire repertoire of miRNA sequences (http://galas.systemsbiology.net/cgi-bin/isomir/find.pl). This enables users to determine the most abundant sequence and the degree of heterogeneity for each individual miRNA species. This information will be useful both to better understand the functions of isomirs and to improve probe or primer design for miRNA detection and measurement.

ChromEval: a software application for the rapid evaluation of HPLC system performance in proteomic applications.

Mass spectrometry-based proteomics is typically performed using high performance liquid chromatography (HPLC) to introduce peptides into the instrument via electrospray ionization. A variety of configurations exist with varying degrees of precision and cost, but the ultimate goal is the reproducible delivery of peptides in well-separated elution peaks. It is well-known that the quality of chromatography can have a dramatic effect on sample identification as well as run-to-run reproducibility, which is especially important for quantitative analyses. Despite the importance of the HPLC system for both shotgun and targeted proteomics, there are few tools available to monitor HPLC performance. In this paper, we describe a new open-source software application, named ChromEval, to allow rapid assessment of HPLC performance, as well as to provide other metrics of mass spectrometer performance, including mass accuracy calibration. ChromEval permits the user to visually monitor the elution of a set of standard peptides in quality control runs interspersed among a regular workflow. To perform these tasks, ChromEval searches mzXML files using Tandem and presents the peptide results in a graphical user interface (GUI) that allows fast assessment of chromatography by visualization of superimposed elution peaks. This tool facilitates the identification and troubleshooting of chromatography problems such as retention time shifts and variance in sample loading due to autosampler error. It also provides crude but consistent metrics of instrument performance including mass accuracy calibration and number of peptides identified from the standard mixture. ChromEval generates easily interpretable data quickly and thereby enables go/no-go decision making during intensive instrument operation.

Correlation between y-type ions observed in ion trap and triple quadrupole mass spectrometers.

Multiple reaction monitoring mass spectrometry (MRM-MS) is a technique for high-sensitivity targeted analysis. In proteomics, MRM-MS can be used to monitor and quantify a peptide based on the production of expected fragment peaks from the selected peptide precursor ion. The choice of which fragment ions to monitor in order to achieve maximum sensitivity in MRM-MS can potentially be guided by existing MS/MS spectra. However, because the majority of discovery experiments are performed on ion trap platforms, there is concern in the field regarding the generalizability of these spectra to MRM-MS on a triple quadrupole instrument. In light of this concern, many operators perform an optimization step to determine the most intense fragments for a target peptide on a triple quadrupole mass spectrometer. We have addressed this issue by targeting, on a triple quadrupole, the top six y-ion peaks from ion trap-derived consensus library spectra for 258 doubly charged peptides from three different sample sets and quantifying the observed elution curves. This analysis revealed a strong correlation between the y-ion peak rank order and relative intensity across platforms. This suggests that y-type ions obtained from ion trap-based library spectra are well-suited for generating MRM-MS assays for triple quadrupoles and that optimization is not required for each target peptide.

MaRiMba: a software application for spectral library-based MRM transition list assembly.

Multiple reaction monitoring mass spectrometry (MRM-MS) is a targeted analysis method that has been increasingly viewed as an avenue to explore proteomes with unprecedented sensitivity and throughput. We have developed a software tool, called MaRiMba, to automate the creation of explicitly defined MRM transition lists required to program triple quadrupole mass spectrometers in such analyses. MaRiMba creates MRM transition lists from downloaded or custom-built spectral libraries, restricts output to specified proteins or peptides, and filters based on precursor peptide and product ion properties. MaRiMba can also create MRM lists containing corresponding transitions for isotopically heavy peptides, for which the precursor and product ions are adjusted according to user specifications. This open-source application is operated through a graphical user interface incorporated into the Trans-Proteomic Pipeline, and it outputs the final MRM list to a text file for upload to MS instruments. To illustrate the use of MaRiMba, we used the tool to design and execute an MRM-MS experiment in which we targeted the proteins of a well-defined and previously published standard mixture.

Rapid optimization of MRM-MS instrument parameters by subtle alteration of precursor and product m/z targets.

Multiple reaction monitoring (MRM) is a highly sensitive method of targeted mass spectrometry (MS) that can be used to selectively detect and quantify peptides based on the screening of specified precursor peptide-to-fragment ion transitions. MRM-MS sensitivity depends critically on the tuning of instrument parameters, such as collision energy and cone voltage, for the generation of maximal product ion signal. Although generalized equations and values exist for such instrument parameters, there is no clear indication that optimal signal can be reliably produced for all types of MRM transitions using such an algorithmic approach. To address this issue, we have devised a workflow functional on both Waters Quattro Premier and ABI 4000 QTRAP triple quadrupole instruments that allows rapid determination of the optimal value of any programmable instrument parameter for each MRM transition. Here, we demonstrate the strategy for the optimizations of collision energy and cone voltage, but the method could be applied to other instrument parameters, such as declustering potential, as well. The workflow makes use of the incremental adjustment of the precursor and product m/z values at the hundredth decimal place to create a series of MRM targets at different collision energies that can be cycled through in rapid succession within a single run, avoiding any run-to-run variability in execution or comparison. Results are easily visualized and quantified using the MRM software package Mr. M to determine the optimal instrument parameters for each transition.

Towards kinetic modeling of global metabolic networks: Methylobacterium extorquens AM1 growth as validation.

Here we report a systematic method for constructing a large scale kinetic metabolic model and its initial application to the modeling of central metabolism of Methylobacterium extorquens AM1, a methylotrophic and environmental important bacterium. Its central metabolic network includes formaldehyde metabolism, serine cycle, citric acid cycle, pentose phosphate pathway, gluconeogensis, PHB synthesis and acetyl-CoA conversion pathway, respiration and energy metabolism. Through a systematic and consistent procedure of finding a set of parameters in the physiological range we overcome an outstanding difficulty in large scale kinetic modeling: the requirement for a massive number of enzymatic reaction parameters. We are able to construct the kinetic model based on general biological considerations and incomplete experimental kinetic parameters. Our method consists of the following major steps: (1) using a generic enzymatic rate equation to reduce the number of enzymatic parameters to a minimum set while still preserving their characteristics; (2) using a set of steady state fluxes and metabolite concentrations in the physiological range as the expected output steady state fluxes and metabolite concentrations for the kinetic model to restrict the parametric space of enzymatic reactions; (3) choosing enzyme constants K's and K'(eqS) optimized for reactions under physiological concentrations, if their experimental values are unknown; (4) for models which do not cover the entire metabolic network of the organisms, designing a dynamical exchange for the coupling between the metabolism represented in the model and the rest not included.

Heat conduction in a two-dimensional harmonic crystal with disorder.

We study the problem of heat conduction in a mass-disordered two-dimensional harmonic crystal. Using two different stochastic heat baths, we perform simulations to determine the system size (L) dependence of the heat current (J). For white noise heat baths we find that J approximately 1/L(alpha) with alpha approximately equal to 0.59, while correlated noise heat baths give alpha approximately equal to 0.51. A special case with correlated disorder is studied analytically and gives alpha=3/2, which agrees also with results from exact numerics.