Removal of a C-terminal serine residue proximal to the inter-chain disulfide bond of a human IgG1 lambda light chain mediates enhanced antibody stability and antibody dependent cell-mediated cytotoxicity

Optimization of biophysical properties is a critical success factor for the developability of monoclonal antibodies with potential therapeutic applications. The inter-domain disulfide bond between light chain (Lc) and heavy chain (Hc) in human IgG1 lends structural support for antibody scaffold stability, optimal antigen binding, and normal Fc function. Recently, human IgG1λ has been suggested to exhibit significantly greater susceptibility to reduction of the inter Lc-Hc disulfide bond relative to the same disulfide bond in human IgG1κ. To understand the molecular basis for this observed difference in stability, the sequence and structure of human IgG1λ and human IgG1κ were compared. Based on this Lc comparison, three single mutations were made in the λ Lc proximal to the cysteine residue, which forms a disulfide bond with the Hc. We determined that deletion of S214 (dS) improved resistance of the association between Lc and Hc to thermal stress. In addition, deletion of this terminal serine from the Lc of IgG1λ provided further benefit, including an increase in stability at elevated pH, increased yield from transient transfection, and improved in vitro antibody dependent cell-mediated cytotoxicity (ADCC). These observations support the conclusion that the presence of the terminal serine of the λ Lc creates a weaker inter-chain disulfide bond between the Lc and Hc, leading to slightly reduced stability and a potential compromise in IgG1λ function. Our data from a human IgG1λ provide a basis for further investigation of the effects of deleting terminal serine from λLc on the stability and function of other human IgG1λ antibodies.     

High-Throughput miRNA and mRNA Sequencing of Paired Colorectal Normal,Tumor and Metastasis Tissues and Bioinformatic Modeling of miRNA-1 Therapeutic Applications

MiRNAs are discussed as diagnostic and therapeutic molecules. However, effective miRNA drug treatments with miRNAs are, so far, hampered by the complexity of the miRNA networks. To identify potential miRNA drugs in colorectal cancer, we profiled miRNA and mRNA expression in matching normal, tumor and metastasis tissues of eight patients by Illumina sequencing. We validated six miRNAs in a large tissue screen containing 16 additional tumor entities and identified miRNA-1, miRNA-129, miRNA-497 and miRNA-215 as constantly de-regulated within the majority of cancers. Of these, we investigated miRNA-1 as representative in a systems-biology simulation of cellular cancer models implemented in PyBioS and assessed the effects of depletion as well as overexpression in terms of miRNA-1 as a potential treatment option. In this system, miRNA-1 treatment reverted the disease phenotype with different effectiveness among the patients. Scoring the gene expression changes obtained through mRNA-Seq from the same patients we show that the combination of deep sequencing and systems biological modeling can help to identify patient-specific responses to miRNA treatments. We present this data as guideline for future pre-clinical assessments of new and personalized therapeutic options.     

Predictors of Raised Viral Load during Antiretroviral Therapy in Patients with and without Prior Antiretroviral Use: A Cross-Sectional Study

Objectives

In Lagos, Nigeria, Médecins Sans Frontières (MSF) and the Ministry of Health (MoH) commenced free antiretroviral treatment (ART) in a hospital-based clinic. We performed a cross-sectional study to compare factors associated with raised viral load between patients with (“experienced”) and without (“naïve”) prior antiretroviral (ARV) exposure at commencement of ART at the clinic. We also examined factors influencing ARV adherence in experienced patients prior to clinic entry.

Methods

We included adult patients receiving ART from MSF who answered a questionnaire about previous antiretroviral use. Multivariate logistic regression was used to estimate odds ratios (OR) for raised viral load (≥1000 copies/mL).

Results

1246 (96%) patients answered: 1075 (86%) reported no, and 171 (14%) some, prior ARV exposure. ARV-naïve patients were more immunosuppressed at baseline: 65% vs 37% (p<0.001) had CD4<200; 17% vs 9% (p = 0.013) were WHO stage 4. Proportionately more experienced than naïve patients had raised viral loads (20% vs 9%, p<0.001) on ART in the MSF/MoH clinic. Raised viral load was associated with prior ARV experience (adjusted OR = 3.74, 95%CI 2.09–6.70, p<0.001) and complete interruption of current ART (adjusted OR = 3.71, 95%CI 2.06–6.68, p<0.001). Higher CD4 at time of VL and a higher self-rated score of recent adherence were associated with lower OR of a raised viral load. Among experienced patients who missed pills before joining MSF/MoH, most common reasons were because ARVS were not affordable (58%) or available (33%), with raised viral load associated with being unsure how to take them (OR = 3.16, 95%CI 1.10–9.12, p = 0.033).

Conclusions

Patients previously exposed to ARVs had increased OR of raised viral load. The cost and availability of ARVs were common reasons for missing ARVs before joining the MSF/MoH clinic, and inadequate patient knowledge was associated with raised viral load.     

The Systemic Immune Network in Recent Onset Type 1 Diabetes: Central Role of Interleukin-1 Receptor Antagonist (DIATOR Trial)

Background

The hypothesis was tested that the systemic immune milieu in recent-onset type 1 diabetes is associated with residual beta cell function and other metabolic patient characteristics.

Methods and Findings

All patients (n = 89, 40% female) of the Diabetes and Atorvastatin (DIATOR) Trial were analyzed at recruitment, i.e. prior to receiving the study medication. Inclusion criteria were insulin dependent diabetes for 2 weeks to 3 months, age range 18–39 years, and islet cell autoantibodies. Blood samples were analyzed for 14 immune mediators by standard methods. Concentrations of all mediators correlated with at least one other mediator (p<0.05, Spearman correlation) giving rise to a network. Interleukin 1 receptor antagonist (IL1-RA) held a central position and was associated with both pro- and anti-inflammatory mediators. Further central elements were the pro-inflammatory mediators CRP and IL-6, the soluble adhesion molecules sICAM-1 and E-selectin, and MCP-4 which held a central position in the chemokine network. The two Th1-associated mediators IFNγ and IP-10 remained outside the network but correlated with each other. All correlations were positive (r = 0.25–0.72), i.e., high levels of pro-inflammatory mediators were accompanied by increased levels of anti-inflammatory mediators. IL-1RA was the only mediator associated with fasting and liquid mixed meal stimulated C-peptide concentrations (r = 0.31 and 0.24, p = 0.003 and 0.025, after adjustment for age, sex, BMI). There were associations between the immune mediator network and BMI (IL-1RA, CRP, IL-6, MCP-4, MIP-1ß) but few or no associations with HbA1c, insulin dose, lipid parameters, age or sex.

Conclusions

In patients with recent onset type 1 diabetes, systemic acute phase proteins, cytokines, chemokines and soluble adhesion molecules form a network. Among the few central elements IL-1RA has a dominant role. IL-1RA is associated with all other groups of mediators and is the only mediator which correlates (positively) with residual beta cell function.

Trial registration

ClinicalTrials.gov registration number: {"type":"clinical-trial","attrs":{"text":"NCT00974740","term_id":"NCT00974740"}}NCT00974740     

Novel Staphylococcal Glycosyltransferases SdgA and SdgB Mediate Immunogenicity and Protection of Virulence-Associated Cell Wall Proteins

Infection of host tissues by Staphylococcus aureus and S. epidermidis requires an unusual family of staphylococcal adhesive proteins that contain long stretches of serine-aspartate dipeptide-repeats (SDR). The prototype member of this family is clumping factor A (ClfA), a key virulence factor that mediates adhesion to host tissues by binding to extracellular matrix proteins such as fibrinogen. However, the biological siginificance of the SDR-domain and its implication for pathogenesis remain poorly understood. Here, we identified two novel bacterial glycosyltransferases, SdgA and SdgB, which modify all SDR-proteins in these two bacterial species. Genetic and biochemical data demonstrated that these two glycosyltransferases directly bind and covalently link N-acetylglucosamine (GlcNAc) moieties to the SDR-domain in a step-wise manner, with SdgB appending the sugar residues proximal to the target Ser-Asp repeats, followed by additional modification by SdgA. GlcNAc-modification of SDR-proteins by SdgB creates an immunodominant epitope for highly opsonic human antibodies, which represent up to 1% of total human IgG. Deletion of these glycosyltransferases renders SDR-proteins vulnerable to proteolysis by human neutrophil-derived cathepsin G. Thus, SdgA and SdgB glycosylate staphylococcal SDR-proteins, which protects them against host proteolytic activity, and yet generates major eptopes for the human anti-staphylococcal antibody response, which may represent an ongoing competition between host and pathogen.     

Pancreatic carcinoma, pancreatitis, and healthy controls: metabolite models in a three-class diagnostic dilemma

Metabolomics as one of the most rapidly growing technologies in the “-omics” field denotes the comprehensive analysis of low molecular-weight compounds and their pathways. Cancer-specific alterations of the metabolome can be detected by high-throughput mass-spectrometric metabolite profiling and serve as a considerable source of new markers for the early differentiation of malignant diseases as well as their distinction from benign states. However, a comprehensive framework for the statistical evaluation of marker panels in a multi-class setting has not yet been established. We collected serum samples of 40 pancreatic carcinoma patients, 40 controls, and 23 pancreatitis patients according to standard protocols and generated amino acid profiles by routine mass-spectrometry. In an intrinsic three-class bioinformatic approach we compared these profiles, evaluated their selectivity and computed multi-marker panels combined with the conventional tumor marker CA 19-9. Additionally, we tested for non-inferiority and superiority to determine the diagnostic surplus value of our multi-metabolite marker panels. Compared to CA 19-9 alone, the combined amino acid-based metabolite panel had a superior selectivity for the discrimination of healthy controls, pancreatitis, and pancreatic carcinoma patients $ [ {\text{volume under ROC surface}}\;\left( {\text{VUS}} \right) = 0. 8 9 1 { }\left( { 9 5\,\% {\text{ CI }}0. 7 9 4- 0. 9 6 8} \right)]. $ We combined highly standardized samples, a three-class study design, a high-throughput mass-spectrometric technique, and a comprehensive bioinformatic framework to identify metabolite panels selective for all three groups in a single approach. Our results suggest that metabolomic profiling necessitates appropriate evaluation strategies and—despite all its current limitations—can deliver marker panels with high selectivity even in multi-class settings.     

High-Throughput Massively Parallel Sequencing for Fetal Aneuploidy Detection from Maternal Plasma

Background

Circulating cell-free (ccf) fetal DNA comprises 3–20% of all the cell-free DNA present in maternal plasma. Numerous research and clinical studies have described the analysis of ccf DNA using next generation sequencing for the detection of fetal aneuploidies with high sensitivity and specificity. We sought to extend the utility of this approach by assessing semi-automated library preparation, higher sample multiplexing during sequencing, and improved bioinformatic tools to enable a higher throughput, more efficient assay while maintaining or improving clinical performance.

Methods

Whole blood (10mL) was collected from pregnant female donors and plasma separated using centrifugation. Ccf DNA was extracted using column-based methods. Libraries were prepared using an optimized semi-automated library preparation method and sequenced on an Illumina HiSeq2000 sequencer in a 12-plex format. Z-scores were calculated for affected chromosomes using a robust method after normalization and genomic segment filtering. Classification was based upon a standard normal transformed cutoff value of z = 3 for chromosome 21 and z = 3.95 for chromosomes 18 and 13.

Results

Two parallel assay development studies using a total of more than 1900 ccf DNA samples were performed to evaluate the technical feasibility of automating library preparation and increasing the sample multiplexing level. These processes were subsequently combined and a study of 1587 samples was completed to verify the stability of the process-optimized assay. Finally, an unblinded clinical evaluation of 1269 euploid and aneuploid samples utilizing this high-throughput assay coupled to improved bioinformatic procedures was performed. We were able to correctly detect all aneuploid cases with extremely low false positive rates of 0.09%, <0.01%, and 0.08% for trisomies 21, 18, and 13, respectively.

Conclusions

These data suggest that the developed laboratory methods in concert with improved bioinformatic approaches enable higher sample throughput while maintaining high classification accuracy.