Development of a novel mammalian display system for selection of antibodies against membrane proteins.

Reliable, specific polyclonal and monoclonal antibodies are important tools in research and medicine. However, the discovery of antibodies against their targets in their native forms is difficult. Here, we present a novel method for discovery of antibodies against membrane proteins in their native configuration in mammalian cells. The method involves the co-expression of an antibody library in a population of mammalian cells that express the target polypeptide within a natural membrane environment on the cell surface. Cells that secrete a single-chain fragment variable (scFv) that binds to the target membrane protein thereby become self-labeled, enabling enrichment and isolation by magnetic sorting and FRET-based flow sorting. Library sizes of up to 109 variants can be screened, thus allowing campaigns of naïve scFv libraries to be selected against membrane protein antigens in a Chinese hamster ovary cell system. We validate this method by screening a synthetic naïve human scFv library against Chinese hamster ovary cells expressing the oncogenic target epithelial cell adhesion molecule and identify a panel of three novel binders to this membrane protein, one with a dissociation constant (KD ) as low as 0.8 nm We further demonstrate that the identified antibodies have utility for killing epithelial cell adhesion molecule-positive cells when used as a targeting domain on chimeric antigen receptor T cells. Thus, we provide a new tool for identifying novel antibodies that act against membrane proteins, which could catalyze the discovery of new candidates for antibody-based therapies.

The social patterning of electronic nicotine delivery system use among US adults.

There is little research examining the social patterning of electronic nicotine delivery system (ENDS) use. This study investigated the association between socioeconomic status (SES) (education, income, and employment status) and current and former ENDS use. Data were collected from 2561 participants from the American Heart Association Tobacco Regulatory and Addiction Center (A-TRAC) online survey. Participants were 18-64 years old and reported demographic, SES, and ENDS use. Poisson regression was used to estimate prevalence ratios (PR 95% confidence interval-CI) of participants' current and former (vs. never) ENDS use. Models were adjusted for age, sex, sexual orientation, race/ethnicity, marital status, and reasons for ENDS use. In the unadjusted analysis, ENDS use was primarily patterned by education and employment status. College educated persons (vs. those with less than a high school diploma) had a 37% greater prevalence of current ENDS use (PR 1.37, 95% CI 1.20-1.55), and a 16% greater prevalence of former ENDS use (PR 1.16, 95% CI 1.06-1.28) in the fully-adjusted model. Persons with household incomes above $90 K (vs. less than $20,000) had a greater prevalence of current (PR 1.30, 95% CI 1.19-1.41) and former (PR 1.17, 95% CI 1.05-1.30) ENDS use. Those who were employed (vs. not employed) had a 13% greater prevalence of current ENDS use (PR 1.13, 95% CI 1.07-1.19) after full adjustment. Higher SES (vs. lower SES) persons were more likely to use ENDS.

Genome sequencing as a generic diagnostic strategy for rare disease.

BACKGROUND: To diagnose the full spectrum of hereditary and congenital diseases, genetic laboratories use many different workflows, ranging from karyotyping to exome sequencing. A single generic high-throughput workflow would greatly increase efficiency. We assessed whether genome sequencing (GS) can replace these existing workflows aimed at germline genetic diagnosis for rare disease. METHODS: We performed short-read GS (NovaSeq™6000; 150 bp paired-end reads, 37 × mean coverage) on 1000 cases with 1271 known clinically relevant variants, identified across different workflows, representative of our tertiary diagnostic centers. Variants were categorized into small variants (single nucleotide variants and indels < 50 bp), large variants (copy number variants and short tandem repeats) and other variants (structural variants and aneuploidies). Variant calling format files were queried per variant, from which workflow-specific true positive rates (TPRs) for detection were determined. A TPR of ≥ 98% was considered the threshold for transition to GS. A GS-first scenario was generated for our laboratory, using diagnostic efficacy and predicted false negative as primary outcome measures. As input, we modeled the diagnostic path for all 24,570 individuals referred in 2022, combining the clinical referral, the transition of the underlying workflow(s) to GS, and the variant type(s) to be detected. RESULTS: Overall, 95% (1206/1271) of variants were detected. Detection rates differed per variant category: small variants in 96% (826/860), large variants in 93% (341/366), and other variants in 87% (39/45). TPRs varied between workflows (79-100%), with 7/10 being replaceable by GS. Models for our laboratory indicate that a GS-first strategy would be feasible for 84.9% of clinical referrals (750/883), translating to 71% of all individuals (17,444/24,570) receiving GS as their primary test. An estimated false negative rate of 0.3% could be expected. CONCLUSIONS: GS can capture clinically relevant germline variants in a 'GS-first strategy' for the majority of clinical indications in a genetics diagnostic lab.

Lentiviral vector packaging and producer cell lines yield titers equivalent to the industry-standard four-plasmid process.

Lentiviral vector (LVV)-mediated cell and gene therapies have the potential to cure diseases that currently require lifelong intervention. However, the requirement for plasmid transfection hinders large-scale LVV manufacture. Moreover, large-scale plasmid production, testing, and transfection contribute to operational risk and the high cost associated with this therapeutic modality. Thus, we developed LVV packaging and producer cell lines, which reduce or eliminate the need for plasmid transfection during LVV manufacture. To develop a packaging cell line, lentiviral packaging genes were stably integrated by random integration of linearized plasmid DNA. Then, to develop EGFP- and anti-CD19 chimeric antigen receptor-encoding producer cell lines, transfer plasmids were integrated by transposase-mediated integration. Single-cell isolation and testing were performed to isolate the top-performing clonal packaging and producer cell lines. Production of LVVs that encode various cargo genes revealed consistency in the production performance of the packaging and producer cell lines compared to the industry-standard four-plasmid transfection method. By reducing or eliminating the requirement for plasmid transfection, while achieving production performance consistent with the current industry standard, the packaging and producer cell lines developed here can reduce costs and operational risks of LVV manufacture, thus increasing patient access to LVV-mediated cell and gene therapies.

High-level production of animal-free recombinant transferrin from Saccharomyces cerevisiae.

BACKGROUND: Animal-free recombinant proteins provide a safe and effective alternative to tissue or serum-derived products for both therapeutic and biomanufacturing applications. While recombinant insulin and albumin already exist to replace their human counterparts in cell culture media, until recently there has been no equivalent for serum transferrin. RESULTS: The first microbial system for the high-level secretion of a recombinant transferrin (rTf) has been developed from Saccharomyces cerevisiae strains originally engineered for the commercial production of recombinant human albumin (Novozymes' Recombumin® USP-NF) and albumin fusion proteins (Novozymes' albufuse®). A full-length non-N-linked glycosylated rTf was secreted at levels around ten-fold higher than from commonly used laboratory strains. Modification of the yeast 2 µm-based expression vector to allow overexpression of the ER chaperone, protein disulphide isomerase, further increased the secretion of rTf approximately twelve-fold in high cell density fermentation. The rTf produced was functionally equivalent to plasma-derived transferrin. CONCLUSIONS: A Saccharomyces cerevisiae expression system has enabled the cGMP manufacture of an animal-free rTf for industrial cell culture application without the risk of prion and viral contamination, and provides a high-quality platform for the development of transferrin-based therapeutics.

Transcript-specific translational regulation in the unfolded protein response of Saccharomyces cerevisiae.

Accumulation of unfolded proteins in the endoplasmic reticulum (ER) causes stress and induces the unfolded protein response (UPR). Genome-wide analysis of translational regulation in response to the UPR-inducing agent dithiothreitol in Saccharomyces cerevisiae is reported. Microarray analysis, confirmed using qRT-PCR, identified transcript-specific translational regulation. Transcripts with functions in ribosomal biogenesis and assembly were translationally repressed. In contrast, mRNAs from known UPR genes, encoding the UPR transcription factor Hac1p, the ER-oxidoreductase Ero1p and the ER-associated protein degradation (ERAD) protein Der1p, were enriched in polysomal fractions, indicating translational up-regulation. Splicing of HAC1 mRNA is shown to be required for efficient ribosomal loading.

Perceived discrimination is associated with health behaviours among African-Americans in the Jackson Heart Study.

BACKGROUND: Using Jackson Heart Study data, we examined associations of multiple measures of perceived discrimination with health behaviours among African-Americans (AA). METHODS: The cross-sectional associations of everyday, lifetime and burden of discrimination with odds of smoking and mean differences in physical activity, dietary fat and sleep were examined among 4925 participants aged 35-84 years after adjustment for age and socioeconomic status (SES). RESULTS: Men reported slightly higher levels of everyday and lifetime discrimination than women and similar levels of burden of discrimination as women. After adjustment for age and SES, everyday discrimination was associated with more smoking and a greater percentage of dietary fat in men and women (OR for smoking: 1.13, 95% CI 1.00 to 1.28 and 1.19, 95% CI 1.05 to 1.34; mean difference in dietary fat: 0.37, p<0.05 and 0.43, p<0.01, in men and women, respectively). Everyday and lifetime discrimination were associated with fewer hours of sleep in men and women (mean difference for everyday discrimination: -0.08, p<0.05 and -0.18, p<0.001, respectively; and mean difference for lifetime discrimination: -0.08, p<0.05 and -0.24, p<0.001, respectively). Burden of discrimination was associated with more smoking and fewer hours of sleep in women only. CONCLUSIONS: Higher levels of perceived discrimination were associated with select health behaviours among men and women. Health behaviours offer a potential mechanism through which perceived discrimination affects health in AA.

Building an automated problem list based on natural language processing: lessons learned in the early phase of development.

Detailed problem lists that comply with JCAHO requirements are important components of electronic health records. Besides improving continuity of care electronic problem lists could serve as foundation infrastructure for clinical trial recruitment, research, biosurveillance and billing informatics modules. However, physicians rarely maintain problem lists. Our team is building a system using MetaMap and UMLS to automatically populate the problem list. We report our early results evaluating the application. Three physicians generated gold standard problem lists for 100 cardiology ambulatory progress notes. Our application had 88% sensitivity and 66% precision using a non-modified UMLS dataset. The systemâs misses concentrated in the group of ambiguous problem list entries (Chi-square=27.12 p<0.0001). In addition to the explicit entries, the notes included 10% implicit entry candidates. MetaMap and UMLS are readily applicable to automate the problem list. Ambiguity in medical documents has consequences for performance evaluation of automated systems.

Natural language processing of clinical trial announcements: exploratory-study of building an automated screening application.

Clinical trials are important for the advancement of medical research. Despite of the benefits clinical trial enrollment is low. We study the feasibility of using NLP to assist with automatic eligibility screening by extracting medical diagnoses from the inclusion and exclusion criteria of cancer clinical trial announcements posted on the internet. We compare the performances of the system versus an oncologist.