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Matkovic, M.

Publications and source records attributed to Matkovic, M..

3 recordsLinked to original sources

Human neutralizing antibodies to cold linear epitopes and to subdomain 1 of SARS-CoV-2

Emergence of SARS-CoV-2 variants diminishes the efficacy of vaccines and antiviral monoclonal antibodies. Continued development of immunotherapies and vaccine immunogens resilient to viral evolution is therefore necessary. Using coldspot-guided antibody discovery, a screening approach that focuses on portions of the virus spike that are both functionally relevant and averse to change, we identified human neutralizing antibodies to highly conserved viral epitopes. Antibody fp.006 binds the fusion peptide and cross-reacts against coronaviruses of the four genera, including the nine human coronaviruses, through recognition of a conserved motif that includes the S2 site of proteolytic cleavage. Antibody hr2.016 targets the stem helix and neutralizes SARS-CoV-2 variants. Antibody sd1.040 binds to subdomain 1, synergizes with antibody rbd.042 for neutralization and, like fp.006 and hr2.016, protects mice when present as bispecific antibody. Thus, coldspot-guided antibody discovery reveals donor-derived neutralizing antibodies that are cross-reactive with Orthocoronavirinae, including SARS-CoV-2 variants. One sentence summaryBroadly cross-reactive antibodies that protect from SARS-CoV-2 variants are revealed by virus coldspot-driven discovery.

immunology↗

Anti-chemokine antibodies after SARS-CoV-2 infection correlate with favorable disease course

Infection by SARS-CoV-2 leads to diverse symptoms, which can persist for months. While antiviral antibodies are protective, those targeting interferons and other immune factors are associated with adverse COVID-19 outcomes. Instead, we discovered that antibodies against specific chemokines are omnipresent after COVID-19, associated with favorable disease, and predictive of lack of long COVID symptoms at one year post infection. Anti-chemokine antibodies are present also in HIV-1 infection and autoimmune disorders, but they target different chemokines than those in COVID-19. Monoclonal antibodies derived from COVID- 19 convalescents that bind to the chemokine N-loop impair cell migration. Given the role of chemokines in orchestrating immune cell trafficking, naturally arising anti-chemokine antibodies associated with favorable COVID-19 may be beneficial by modulating the inflammatory response and thus bear therapeutic potential. One-Sentence SummaryNaturally arising anti-chemokine antibodies associate with favorable COVID-19 and predict lack of long COVID.

immunology↗

Machine learning predicts immunoglobulin light chain toxicity through somatic mutations

In systemic light chain amyloidosis (AL), pathogenic monoclonal immunoglobulin light chains (LCs) form toxic aggregates and amyloid fibrils in target organs. Prompt diagnosis is crucial to avoid permanent organ damage. However, delays in diagnosis are common, with a consequent poor patients prognosis, as symptoms usually appear only after strong organ involvement. Here, we present LICTOR, a machine learning approach predicting LC toxicity in AL, based on the distribution of somatic mutations acquired during clonal selection. LICTOR achieved a specificity and a sensitivity of 0.82 and 0.76, respectively, with an area under the receiver operating characteristic curve (AUC) of 0.87. Tested on an independent set of 12 LCs sequences with known clinical phenotypes, LICTOR achieved a prediction accuracy of 83%. Furthermore, we were able to abolish the toxic phenotype of an LC by in silico reverting two germline-specific somatic mutations identified by LICTOR and by experimentally assessing the loss of in vivo toxicity in a Caenorhabditis elegans model. Therefore, LICTOR represents a promising strategy for AL diagnosis and reducing high mortality rates in AL.

bioinformatics↗