Fc-engineered antibodies promote neutrophil-dependent control of Mycobacterium tuberculosis.

Mounting evidence indicates that antibodies can contribute towards control of tuberculosis (TB). However, the underlying mechanisms of humoral immune protection and whether antibodies can be exploited in therapeutic strategies to combat TB are relatively understudied. Here we engineered the receptor-binding Fc (fragment crystallizable) region of an antibody recognizing the Mycobacterium tuberculosis (Mtb) capsule, to define antibody Fc-mediated mechanism(s) of Mtb restriction. We generated 52 Fc variants that either promote or inhibit specific antibody effector functions, rationally building antibodies with enhanced capacity to promote Mtb restriction in a human whole-blood model of infection. While there is likely no singular Fc profile that universally drives control of Mtb, here we found that several Fc-engineered antibodies drove Mtb restriction in a neutrophil-dependent manner. Single-cell RNA sequencing analysis showed that a restrictive Fc-engineered antibody promoted neutrophil survival and expression of cell-intrinsic antimicrobial programs. These data show the potential of Fc-engineered antibodies as therapeutics able to harness the protective functions of neutrophils to promote control of TB.

Distinctive antibody responses to Mycobacterium tuberculosis in pulmonary and brain infection.

Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), remains a global health burden. While Mtb is primarily a respiratory pathogen, it can spread to other organs, including the brain and meninges, causing TB meningitis (TBM). However, little is known about the immunological mechanisms that leads to differential disease across organs. Attention has focused on differences in T cell responses in the control of Mtb in the lungs, but emerging data point to a role for antibodies, as both biomarkers of disease control and as antimicrobial molecules. Given an increasing appreciation for compartmentalized antibody responses across the blood brain barrier, here we characterized the antibody profiles across the blood and brain compartments during TBM, and determined whether Mtb-specific humoral immune responses differed between Mtb infection of the lung (pulmonary TB) and TBM. Using a high throughput systems serology approach, we deeply profiled the antibody responses against 10 different Mtb antigens, including lipoarabinomannan (LAM) and purified protein derivative (PPD), in HIV-negative adults with pulmonary TB (n=10) vs TBM (n=60). Antibody studies included analysis of immunoglobulin isotypes (IgG, IgM, IgA) and subclass levels (IgG1-4), the capacity of Mtb-specific antibodies to bind to Fc receptors or C1q, and to activate innate immune effectors functions (complement and NK cells activation, monocyte or neutrophil phagocytosis). Machine learning methods were applied to characterize serum and CSF responses in TBM, identify prognostic factors associated with disease severity, and define the key antibody features that distinguish TBM from pulmonary TB. In individuals with TBM, we identified CSF-specific antibody profiles that marked a unique and compartmentalized humoral response against Mtb, characterized by an enrichment of Mtb-specific antibodies able to robustly activate complement and drive phagocytosis by monocytes and neutrophils, all of which were associated with milder TBM severity at presentation. Moreover, individuals with TBM exhibited Mtb-specific antibodies in the serum with an increased capacity to activate phagocytosis by monocytes, compared to individuals with pulmonary TB, despite having lower IgG titers and Fcγ receptors (FcγR)-binding capacity. Collectively, these data point to functionally divergent humoral responses depending on the site of infection (i.e. lungs vs brain), and demonstrate a highly compartmentalized Mtb-specific antibody response within the CSF during TBM. Moreover, our results suggest that phagocytosis- and complement-mediating antibodies may promote attenuated neuropathology and milder TBM disease.

Advancing Antibody Engineering through Synthetic Evolution and Machine Learning.

Abs are versatile molecules with the potential to achieve exceptional binding to target Ags, while also possessing biophysical properties suitable for therapeutic drug development. Protein display and directed evolution systems have transformed synthetic Ab discovery, engineering, and optimization, vastly expanding the number of Ab clones able to be experimentally screened for binding. Moreover, the burgeoning integration of high-throughput screening, deep sequencing, and machine learning has further augmented in vitro Ab optimization, promising to accelerate the design process and massively expand the Ab sequence space interrogated. In this Brief Review, we discuss the experimental and computational tools employed in synthetic Ab engineering and optimization. We also explore the therapeutic challenges posed by developing Abs for infectious diseases, and the prospects for leveraging machine learning-guided protein engineering to prospectively design Abs resistant to viral escape.