Characterization of SARS-CoV-2 Convalescent Patients' Serological Repertoire Reveals High Prevalence of Iso-RBD Antibodies.

While our understanding of SARS-CoV-2 pathogenesis and antibody responses following infection and vaccination has improved tremendously since the outbreak in 2019, the sequence identities and relative abundances of the individual constituent antibody molecules in circulation remain understudied. Using Ig-Seq, we proteomically profiled the serological repertoire specific to the whole ectodomain of SARS-CoV-2 prefusion-stabilized spike (S) as well as to the receptor binding domain (RBD) over a 6-month period in four subjects following SARS-CoV-2 infection before SARS-CoV-2 vaccines were available. In each individual, we identified between 59 and 167 unique IgG clonotypes in serum. To our surprise, we discovered that ∼50% of serum IgG specific for RBD did not recognize prefusion-stabilized S (referred to as iso-RBD antibodies), suggesting that a significant fraction of serum IgG targets epitopes on RBD inaccessible on the prefusion-stabilized conformation of S. On the other hand, the abundance of iso-RBD antibodies in nine individuals who received mRNA-based COVID-19 vaccines encoding prefusion-stabilized S was significantly lower (∼8%). We expressed a panel of 12 monoclonal antibodies (mAbs) that were abundantly present in serum from two SARS-CoV-2 infected individuals, and their binding specificities to prefusion-stabilized S and RBD were all in agreement with the binding specificities assigned based on the proteomics data, including 1 iso-RBD mAb which bound to RBD but not to prefusion-stabilized S. 2 of 12 mAbs demonstrated neutralizing activity, while other mAbs were non-neutralizing. 11 of 12 mAbs also bound to S (B.1.351), but only 1 maintained binding to S (B.1.1.529). This particular mAb binding to S (B.1.1.529) 1) represented an antibody lineage that comprised 43% of the individual's total S-reactive serum IgG binding titer 6 months post-infection, 2) bound to the S from a related human coronavirus, HKU1, and 3) had a high somatic hypermutation level (10.9%), suggesting that this antibody lineage likely had been elicited previously by pre-pandemic coronavirus and was re-activated following the SARS-CoV-2 infection. All 12 mAbs demonstrated their ability to engage in Fc-mediated effector function activities. Collectively, our study provides a quantitative overview of the serological repertoire following SARS-CoV-2 infection and the significant contribution of iso-RBD antibodies, demonstrating how vaccination strategies involving prefusion-stabilized S may have reduced the elicitation of iso-RBD serum antibodies which are unlikely to contribute to protection.

An Immunoproteomic Survey of the Antibody Landscape: Insights and Opportunities Revealed by Serological Repertoire Profiling.

Immunoproteomics has emerged as a versatile tool for analyzing the antibody repertoire in various disease contexts. Until recently, characterization of antibody molecules in biological fluids was limited to bulk serology, which identifies clinically relevant features of polyclonal antibody responses. The past decade, however, has seen the rise of mass-spectrometry-enabled proteomics methods that have allowed profiling of the antibody response at the molecular level, with the disease-specific serological repertoire elucidated in unprecedented detail. In this review, we present an up-to-date survey of insights into the disease-specific immunological repertoire by examining how quantitative proteomics-based approaches have shed light on the humoral immune response to infection and vaccination in pathogenic illnesses, the molecular basis of autoimmune disease, and the tumor-specific repertoire in cancer. We address limitations of this technology with a focus on emerging potential solutions and discuss the promise of high-resolution immunoproteomics in therapeutic discovery and novel vaccine design.

Measuring and modeling energy and power consumption in living microbial cells with a synthetic ATP reporter.

BACKGROUND: Adenosine triphosphate (ATP) is the main energy carrier in living organisms, critical for metabolism and essential physiological processes. In humans, abnormal regulation of energy levels (ATP concentration) and power consumption (ATP consumption flux) in cells is associated with numerous diseases from cancer, to viral infection and immune dysfunction, while in microbes it influences their responses to drugs and other stresses. The measurement and modeling of ATP dynamics in cells is therefore a critical component in understanding fundamental physiology and its role in pathology. Despite the importance of ATP, our current understanding of energy dynamics and homeostasis in living cells has been limited by the lack of easy-to-use ATP sensors and the lack of models that enable accurate estimates of energy and power consumption related to these ATP dynamics. Here we describe a dynamic model and an ATP reporter that tracks ATP in E. coli over different growth phases. RESULTS: The reporter is made by fusing an ATP-sensing rrnB P1 promoter with a fast-folding and fast-degrading GFP. Good correlations between reporter GFP and cellular ATP were obtained in E. coli growing in both minimal and rich media and in various strains. The ATP reporter can reliably monitor bacterial ATP dynamics in response to nutrient availability. Fitting the dynamics of experimental data corresponding to cell growth, glucose, acetate, dissolved oxygen, and ATP yielded a mathematical and circuit model. This model can accurately predict cellular energy and power consumption under various conditions. We found that cellular power consumption varies significantly from approximately 0.8 and 0.2 million ATP/s for a tested strain during lag and stationary phases to 6.4 million ATP/s during exponential phase, indicating ~ 8-30-fold changes of metabolic rates among different growth phases. Bacteria turn over their cellular ATP pool a few times per second during the exponential phase and slow this rate by ~ 2-5-fold in lag and stationary phases. CONCLUSION: Our rrnB P1-GFP reporter and kinetic circuit model provide a fast and simple way to monitor and predict energy and power consumption dynamics in bacterial cells, which can impact fundamental scientific studies and applied medical treatments in the future.