Molecular Biotechnology @ Tessier lab

Our mission

The Tessier lab aims to develop best-in-class therapeutic antibodies and apply them to address multiple key biomedical challenges: 

1. Bispecific antibodies for brain delivery of biologics, including antibodies (agonists and antagonists), cytokines, and gene silencing agents

2. Therapeutic brain drug delivery applications, including treating neurodegenerative (Alzheimer's and Parkinson's disease) and autoimmune (Multiple Sclerosis) disorders, brain cancer and acute disorders (Traumatic Brain Injury)

3. Conformational antibodies for detecting and treating neurodegenerative disorders

4. Non-invasive methods for modulating gene expression in the brain

5 Antibody-drug conjugates for treating cancer and gene silencing applications

6. Agonist and bispecific antibodies that activate T cells for treating cancer

To accomplish this, we develop next-generation technologies for designing, discovering, engineering, characterizing, formulating, and delivering therapeutic antibodies. Our technology development efforts are focused in three main areas: 

1. Protein engineering and directed evolution 

2. Biomolecular screening and high-throughput characterization 

3. Machine learning, artificial intelligence, and computational predictions

Our interdisciplinary research program uses experimental and computational approaches for generating new fundamental insights into antibody structure and function, molecular origins of protein-protein interactions, and molecular determinants of key antibody properties (stability, solubility, specificity, and affinity). Our development of novel high-throughput screening and machine-learning methods is focused on discovering therapeutic antibody candidates with drug-like properties.

Recent Highlights

Research paper: Bispecific antibody shuttles targeting CD98hc mediate efficient and long-lived brain delivery of IgGs (Oct 2023). [link] [news story]

Research paper: Optimization of therapeutic antibodies for reduced self-association and non-specific binding using interpretable machine learning (Nat Biomed Eng, Sept 2023). [link] [news story

Lab has open postdoc positions related to antibody drug development, brain delivery, biophysical analysis of antibody therapeutic candidates, high-throughput antibody screening, antibody formulation and stability, and computational predictions of antibody developability properties (self-association, viscosity and aggregation). Interested candidates with expertise in one or more areas related to protein biochemistry, biophysics, molecular biology, protein expression and purification, and/or computational methods should contact Dr. Tessier (ptessier@umich.edu) for more information. (September 2023)

Lab receives NIH R01 to support its development of bispecific antibodies for delivering neuroprotective antibodies to the brain (May 2023) [link] [press release]

Lab receives NIH R21 to support its development of bispecific antibody conjugates for non-invasive neuronal gene silencing (May 2023) [link

Research paper: Reduction of therapeutic antibody self-association using yeast-display selections and machine learning (mAbs, Nov 2022). [link] [press release]

Review paper: Unlocking the potential of agonist antibodies for treating cancer using antibody engineering (Trends Mol Med, Nov 2022). [link]

Tessier presents about machine learning-guided antibody engineering at the Antibody Society's Biopharmaceutical Informatics Symposium (Sept 2022). [link] [lecture video] 

Research paper: Co-optimization of therapeutic antibody affinity and specificity using machine learning models that generalize to novel mutational space (Nat Commun, Jun 2022). [link] [blog] [press release]

Research paper: Mutational analysis of SARS-CoV-2 Variants of Concern reveals key tradeoffs between receptor affinity and antibody escape (PLOS Comput Biol, May 2022). [link]

Tessier to serve as vice-chair of 2nd Gordon Conference on Biotherapeutics and Vaccines Development (Mar 2022). [link]

Research paper: Rapid and quantitative in vitro evaluation of SARS-CoV-2 neutralizing antibodies and nanobodies (Anal Chem, Feb 2022). [link]

Research paper: Antibodies with weakly basic isoelectric points minimize trade-offs between formulation and physiological colloidal properties (Mol Pharm, Feb 2022). [link]

Protocol paper: Isolating high-affinity nanobodies using CDR-swapping mutagenesis (STAR Protoc, Feb 2022). [link]

Review paper: Improving antibody drug development using bionanotechnology (Curr Opin Biotech, Feb 2022). [link]

Review paper: Agonist antibody discovery: experimental, computational and rational engineering approaches (Drug Discov Today, Jan 2022). [link]

Research paper: Discovery of monoclonal antibodies that potently inhibit SARS-CoV-2 using single B cell screening (Sci Rep, Oct 2021) [link]

Research paper: Engineered multivalent nanobodies potently and broadly neutralize SARS-CoV-2 variants (Adv Ther, Aug 2021) [link]

Research paper: Novel protein engineering method for generating potent SARS-CoV-2 neutralizing nanobodies (Cell Chem Biol, Jun 2021) [link] [news story]

Lab member Emily Makowski receives an NIH Pharmacological Sciences  (T32) Fellowship (June 2021) [link]

Research paper: Ultradilute measurements of antibody self-association are predictive of formulation properties (viscosity and opalescence) at high concentrations (Mol Pharm, May 2021) [link]

Research paper: Discovery of Alzheimer's antibodies with better combinations of binding properties than multiple clinical-stage antibodies (aducanumab and crenezumab; J Biol Chem, Mar 2021) [link]

Lab receives Department of Defense grant to engineer next-generation antibody-drug conjugates (Jan 2021)

Research paper: Discovery of conformational antibodies for detecting peptide aggregates in therapeutic drug formulations (Biotech Bioeng, Oct 2020) [link]

Lab publishes a review paper on drug-like multispecific antibodies (Int J Mol Sci, Oct 2020). [link]

Research paper: First computational method for identifying antibodies with drug-like specificity and low risk for non-specific and self-interactions (Mol Pharm, Jun 2020) [link]

Discovery of a nature-inspired approach for designing conformational antibodies specific for pathological protein aggregates is featured in a special issue of the Journal of Biological Chemistry on antibody engineering (Mar 2020) [link]

Lab reports (in collaboration with the Georgiou lab at UT Austin) an engineered Fc domain for ultra-long circulation persistence (Nat Commun, Nov 2019) [link]

Lab discovers unique impacts of different chemical modifications (oxidation and deamidation) on antibody physical stability (J Pharm Sci, Oct 2019) [link]

Lab publishes a review paper on protein activity/stability trade-offs in a special issue of AIChE Journal honoring Frances Arnold's Nobel Prize (Oct 2019) [link]

Lab member Lina Wu receives an NIH Cellular Biotechnology (T32) Fellowship (July 2019)

Lab reports novel conformational antibodies that are highly sensitive for detecting aggregates in peptide drug formulations (Biotech Bioeng, April 2019) [link]

Lab member Matthew Smith receives an NSF Graduate Research Fellowship (Apr 2019) [link]

Lab discovers a nature-inspired approach for designing conformational antibodies specific for pathological protein aggregates (J Biol Chem, March 2019) [link]

Lab identifies important impacts of a common chemical modification (deamidation) on antibody stability and aggregation (Mol Pharm, March 2019) [link]

Lab reports key physicochemical determinants of drug-like antibodies with high specificity (Protein Eng Des Sel, Feb 2019) [link]

Lab publishes a review paper on selecting and engineering antibodies with drug-like specificity (Curr Opin Biotechnol, Feb 2019) [link]