Publications

Publications through Stanford Center for Human Systems Immunology

A short list of key publications is listed below.

2019

  • – American Chemical Society

    Universal Scaling Behavior during Network Formation in Controlled Radical Polymerizations

    Despite the ubiquity of branched and network polymers in biological, electronic, and rheological applications, it remains difficult to predict the network structure arising from polymerization of vinyl and multivinyl monomers. While controlled radical polymerization (CRP) techniques afford modularity and control in the synthesis of (hyper)branched polymers, a unifying understanding of network formation providing grounded predictive power is still lacking. A current limitation is the inability to predict the number and weight average molecular weights that arise during the synthesis of (hyper)branched polymers using CRP. This study addresses this literature gap through first building intuition via a growth boundary analysis on how certain environmental cues (concentration, monomer choice, and cross-linker choice) affect the cross-link efficiency during network formation through experimental gel point measurements.

  • – Wiley Online Library

    A Nanoparticle Platform for Improved Potency, Stability, and Adjuvanticity of Poly(I:C)

    Cancer immunotherapies and prophylactic vaccines against infectious diseases often exploit adjuvants such as toll‐like receptor agonists (TLRa) to drive potent and directed immune responses. Unfortunately, a promising class of TLRa based on nucleic acid derivatives is susceptible to degradation by nucleases, cause life‐threatening systemic toxicities, and is difficult to target to specific cell populations or tissues within the body. In this study a library of cationic polymeric nanoparticles (NP) is developed for encapsulation and delivery of the double‐stranded RNA structural mimic, poly(I:C) (pIC), to address these limitations.

  • – American Institute of Chemical Engineers

    Injectable supramolecular polymer–nanoparticle hydrogels enhance human mesenchymal stem cell delivery

    Stem cell therapies have emerged as promising treatments for injuries and diseases in regenerative medicine. Yet, delivering stem cells therapeutically can be complicated by invasive administration techniques, heterogeneity in the injection media, and/or poor cell retention at the injection site. Despite these issues, traditional administration protocols using bolus injections in a saline solution or surgical implants of cell‐laden hydrogels have highlighted the promise of cell administration as a treatment strategy. To address these limitations, we have designed an injectable polymer–nanoparticle (PNP) hydrogel platform exploiting multivalent, noncovalent interactions between modified biopolymers and biodegradable nanoparticles for encapsulation and delivery of human mesenchymal stem cells (hMSCs).

  • – Frontiers

    Increased T Cell Differentiation and Cytolytic Function in Bangladeshi Compared to American Children

    During the first 5 years of life, children are especially vulnerable to infection-related morbidity and mortality. Conversely, the Hygiene Hypothesis suggests that a lack of exposure to infectious agents early in life could explain the increasing incidence of allergies and autoimmunity in high-income countries. Understanding these phenomena, however, is hampered by a lack of comprehensive, direct immune monitoring in children with differing degrees of microbial exposure. Using mass cytometry, we provide an in-depth profile of the peripheral blood mononuclear cells (PBMCs) of children in regions at the extremes of exposure: the San Francisco Bay Area, USA and an economically poor district of Dhaka, Bangladesh.

  • – A Multiscale Model for Solute Diffusion in Hydrogels

    A Multiscale Model for Solute Diffusion in Hydrogels

    The number of biomedical applications of hydrogels is increasing rapidly on account of their unique physical, structural, and mechanical properties. The utility of hydrogels as drug delivery systems or tissue engineering scaffolds critically depends on the control of diffusion of solutes through the hydrogel matrix. Predicting or even modeling this diffusion is challenging due to the complex structure of hydrogels. Currently, the diffusivity of solutes in hydrogels is typically modeled by one of three main theories proceeding from distinct diffusion mechanisms: (i) hydrodynamic, (ii) free volume, and (iii) obstruction theory. Yet, a comprehensive predictive model is lacking. Thus, time and capital-intensive trial-and-error procedures are used to test the viability of hydrogel applications. In this work, we have developed a model for the diffusivity of solutes in hydrogels combining the three main theoretical frameworks, which we call the multiscale diffusion model (MSDM).


2018

  • – OUP Academic

    High Rates of Enteric Fever Diagnosis and Lower Burden of Culture-Confirmed Disease in Peri-urban and Rural Nepal

    In South Asia, data on enteric fever are sparse outside of urban areas. We characterized enteric fever diagnosis patterns and the burden of culture-confirmed cases in peri-urban and rural Nepal.

  • – Wiley Online Library

    Non‐Newtonian Polymer–Nanoparticle Hydrogels Enhance Cell Viability during Injection

    Drug delivery and cell transplantation require minimally invasive deployment strategies such as injection through clinically relevant high‐gauge needles. Supramolecular hydrogels comprising dodecyl‐modified hydroxypropylmethylcellulose and poly(ethylene glycol)‐block‐poly(lactic acid) have been previously demonstrated for the delivery of drugs and proteins. Here, it is demonstrated that the rheological properties of these hydrogels allow for facile injectability, an increase of cell viability after injection when compared to cell viabilities of cells injected in phosphate‐buffered saline, and homogeneous cell suspensions that do not settle.

  • – Cell

    A Structured Tumor-Immune Microenvironment in Triple Negative Breast Cancer Revealed by Multiplexed Ion Beam Imaging

    The immune system is critical in modulating cancer progression, but knowledge of immune composition, phenotype, and interactions with tumor is limited. We used multiplexed ion beam imaging by time-of-flight (MIBI-TOF) to simultaneously quantify in situ expression of 36 proteins covering identity, function, and immune regulation at sub-cellular resolution in 41 triple-negative breast cancer patients.

  • – Nature

    A multi-cohort study of the immune factors associated with M. tuberculosis infection outcomes

    Most infections with Mycobacterium tuberculosis (Mtb) manifest as a clinically asymptomatic, contained state, known as latent tuberculosis infection, that affects approximately one-quarter of the global population1. Although fewer than one in ten individuals eventually progress to active disease2, tuberculosis is a leading cause of death from infectious disease worldwide3. Despite intense efforts, immune factors that influence the infection outcomes remain poorly defined. Here we used integrated analyses of multiple cohorts to identify stage-specific host responses to Mtb infection.

  • – Cell

    Deep Profiling of Mouse Splenic Architecture with CODEX Multiplexed Imaging

    A highly multiplexed cytometric imaging approach, termed co-detection by indexing (CODEX), is used here to create multiplexed datasets of normal and lupus (MRL/lpr) murine spleens. CODEX iteratively visualizes antibody binding events using DNA barcodes, fluorescent dNTP analogs, and an in situ polymerization-based indexing procedure. An algorithmic pipeline for single-cell antigen quantification in tightly packed tissues was developed and used to overlay well-known morphological features with de novo characterization of lymphoid tissue architecture at a single-cell and cellular neighborhood levels.


2017

  • – Nature

    Identifying specificity groups in the T cell receptor repertoire

    T cell receptor (TCR) sequences are very diverse, with many more possible sequence combinations than T cells in any one individual1–4. Here we define the minimal requirements for TCR antigen specificity, through an analysis of TCR sequences using a panel of peptide and major histocompatibility complex (pMHC)-tetramer-sorted cells and structural data.

  • – OUP Academic

    Validation of the Sepsis MetaScore for Diagnosis of Neonatal Sepsis

    Neonates are at increased risk for developing sepsis, but this population often exhibits ambiguous clinical signs that complicate the diagnosis of infection. No biomarker has yet shown enough diagnostic accuracy to rule out sepsis at the time of clinical suspicion.


– LWW

Benchmarking Sepsis Gene Expression Diagnostics Using Public Data

In response to a need for better sepsis diagnostics, several new gene expression classifiers have been recently published, including the 11-gene “Sepsis MetaScore,” the “FAIM3-to-PLAC8” ratio, and the Septicyte Lab. We performed a systematic search for publicly available gene expression data in sepsis and tested each gene expression classifier in all included datasets. We also created a public repository of sepsis gene expression data to encourage their future reuse.

2016

  • – JCI Insight

    Integrated, multicohort analysis of systemic sclerosis identifies robust transcriptional signature of disease severity

    Systemic sclerosis (SSc) is a rare autoimmune disease with the highest case-fatality rate of all connective tissue diseases. Current efforts to determine patient response to a given treatment using the modified Rodnan skin score (mRSS) are complicated by interclinician variability, confounding, and the time required between sequential mRSS measurements to observe meaningful change. There is an unmet critical need for an objective metric of SSc disease severity.

  • – OUP Academic

    Methods to increase reproducibility in differential gene expression via meta-analysis

    Findings from clinical and biological studies are often not reproducible when tested in independent cohorts. Due to the testing of a large number of hypotheses and relatively small sample sizes, results from whole-genome expression studies in particular are often not reproducible. Compared to single-study analysis, gene expression meta-analysis can improve reproducibility by integrating data from multiple studies. However, there are multiple choices in designing and carrying out a meta-analysis. Yet, clear guidelines on best practices are scarce. Here, we hypothesized that studying subsets of very large meta-analyses would allow for systematic identification of best practices to improve reproducibility.


– Science Translational Medicine

Robust classification of bacterial and viral infections via integrated host gene expression diagnostics

Sepsis, a severe inflammation caused by infection, is a common and deadly medical condition. Sepsis therapy combines supportive treatment with interventions directed at the underlying cause of the illness, especially antibiotics for bacterial infections. Unfortunately, it can be difficult to distinguish patients with noninfectious inflammation from those with bacterial and viral infections, and only those with bacterial sepsis derive any benefit from antibiotics. Sweeney et al. have previously analyzed large numbers of patients across many cohorts to derive a blood test identifying which patients with sepsis-like symptoms have an underlying infection. Now, the authors expanded their analysis to create an integrated score that not only identifies infected patients but also classifies their infection as bacterial or viral, suggesting appropriate treatment.


– PNAS

Successful immunotherapy induces previously unidentified allergen-specific CD4+ T-cell subsets

The mechanisms through which successful immunotherapy induces possible deletion, replacement, or reprogramming of T cells are unknown. By evaluating the expression of T-cell–related genes, and using appropriate multivariate statistical approaches, our data show that successful immunotherapy can induce previously unidentified CD4+ T-cell subtypes during treatment that could help to predict an “immune-tolerant” clinical phenotype identified after cessation of treatment. The ability to use “anergic” transcriptional phenotypes in single T cells to predict successful “immune tolerance” induction in the clinic setting, as suggested by our findings, could lead to transformative impacts in the field of immunotherapy.


– The Lancet Respiratory Medicine

Genome-wide expression for diagnosis of pulmonary tuberculosis: a multicohort analysis

Active pulmonary tuberculosis is difficult to diagnose and treatment response is difficult to effectively monitor. A WHO consensus statement has called for new non-sputum diagnostics. The aim of this study was to use an integrated multicohort analysis of samples from publically available datasets to derive a diagnostic gene set in the peripheral blood of patients with active tuberculosis.


– Cell Reports

Host-Microbiota Interactions in the Pathogenesis of Antibiotic-Associated Diseases

Lichtman et al. compared longitudinal mouse models of antibiotic-associated inflammation. By concurrently measuring gut microbes and secreted host proteins with 16S rRNA sequencing and mass spectrometry, they found dynamic, yet distinct, microbe and proteome profiles. Inflammation-regulated proteases, antimicrobial proteins, and immunoglobulins marked multiple pathways actively shaping host responses to dysbiosis.

2015

  • – Immunity

    Integrated, Multi-cohort Analysis Identifies Conserved Transcriptional Signatures across Multiple Respiratory Viruses

    Clinically relevant respiratory viral signatures have not been defined. Khatri and colleagues identified host transcriptional responses common to multiple respiratory viruses (MVS) or specific to influenza (IMS) by leveraging heterogeneity present in public datasets. Both signatures distinguish viral from bacterial infections and IMS also distinguishes influenza from other viral infections.

  • – American Journal of Respiratory and Critical Care Medicine

    Comprehensive Validation of the FAIM3:PLAC8 Ratio in Time-matched Public Gene Expression Data | American Journal of Respiratory and Critical Care Medicine

    Scicluna and colleagues recently reported the gene expression ratio of Fas apoptotic inhibitory molecule 3 (FAIM3) to placenta-specific 8 (PLAC8) as a new sepsis diagnostic biomarker (1). Accurate sepsis diagnosis is critical, as the mortality rate of sepsis increases for each hour that antibiotics are not administered (2). The FAIM3:PLAC8 ratio was discovered in a cohort comparing critically ill patients within 24 hours of admission for community-acquired pneumonia with noninfected patients. Scicluna and colleagues found that the FAIM3:PLAC8 ratio had areas under the receiver operating characteristic curve (AUCs) of 0.845 and 0.784 for diagnosing community-acquired pneumonia in their discovery and validation cohorts, respectively (1).

2014

  • – Nature Biotechnology

    Linking T-cell receptor sequence to functional phenotype at the single-cell level

    Although each T lymphocyte expresses a T-cell receptor (TCR) that recognizes cognate antigen and controls T-cell activation, different T cells bearing the same TCR can be functionally distinct. Each TCR is a heterodimer, and both α- and β-chains contribute to determining TCR antigen specificity. Here we present a methodology enabling integration of information about TCR specificity with information about T cell function.