Glycosylation is one of the most important post-translational modifications found in nature. Identifying and characterizing glycans is an important step in correlating glycosylation structure to the glycan's function, both in normal glycoproteins and those that are modified in a disease state. Glycans on a protein can be characterized by a variety of methods. This review focuses on the mass spectral analysis of glycopeptides, after subjecting the glycoprotein to proteolysis. This analytical approach is useful in characterizing glycan heterogeneity and correlating glycan compositions to their attachment sites on the protein. The information obtained from this approach can serve as the foundation for understanding how glycan compositions affect protein function, in both normal and aberrant glycoproteins.

The human immunodeficiency virus type 1 (HIV-1) envelope glycoprotein (Env) trimer, which consists of the gp120 and gp41 subunits, is the focus of multiple strategies for vaccine development. Extensive Env glycosylation provides HIV-1 with protection from the immune system, yet the glycans are also essential components of binding epitopes for numerous broadly neutralizing antibodies. Recent studies have shown that when Env is isolated from virions, its glycosylation profile differs significantly from that of soluble forms of Env (gp120 or gp140) predominantly used in vaccine discovery research. Here we show that exogenous membrane-anchored Envs, which can be produced in large quantities in mammalian cells, also display a virion-like glycan profile, where the glycoprotein is extensively decorated with high-mannose glycans. Additionally, because we characterized the glycosylation with a high-fidelity profiling method, glycopeptide analysis, an unprecedented level of molecular detail regarding membrane Env glycosylation and its heterogeneity is presented. Each glycosylation site was characterized individually, with about 500 glycoforms characterized per Env protein. While many of the sites contain exclusively high-mannose glycans, others retain complex glycans, resulting in a glycan profile that cannot currently be mimicked on soluble gp120 or gp140 preparations. These site-level studies are important for understanding antibody-glycan interactions on native Env trimers. Additionally, we report a newly observed O -linked glycosylation site, T606, and we show that the full O -linked glycosylation profile of membrane-associated Env is similar to that of soluble gp140. These findings provide new insight into Env glycosylation and clarify key molecular-level differences between membrane-anchored Env and soluble gp140. IMPORTANCE A vaccine that protects against human immunodeficiency virus type 1 (HIV-1) infection should elicit antibodies that bind to the surface envelope glycoproteins on the membrane of the virus. The envelope glycoproteins have an extensive coat of carbohydrates (glycans), some of which are recognized by virus-neutralizing antibodies and some of which protect the virus from neutralizing antibodies. We found that the HIV-1 membrane envelope glycoproteins have a unique pattern of carbohydrates, with many high-mannose glycans and also, in some places, complex glycans. This pattern was very different from the carbohydrate profile seen for a more easily produced soluble version of the envelope glycoprotein. Our results provide a detailed characterization of the glycans on the natural membrane envelope glycoproteins of HIV-1, a carbohydrate profile that would be desirable to mimic with a vaccine.

The analysis of HIV-1 envelope carbohydrates is critical to understanding their roles in HIV-1 transmission as well as in binding of envelope to HIV-1 antibodies. However, direct analysis of protein glycosylation by glycopeptide-based mass mapping approaches involves structural simplification of proteins with the use of a protease followed by an isolation and/or enrichment step before mass analysis. The successful completion of glycosylation analysis is still a major analytical challenge due to the complexity of samples, wide dynamic range of glycopeptide concentrations, and glycosylation heterogeneity. Here, we use a novel experimental workflow that includes an up-front complete or partial enzymatic deglycosylation step before trypsin digestion to characterize the glycosylation patterns and maximize the glycosylation coverage of two recombinant HIV-1 transmitted/founder envelope oligomers derived from clade B and C viruses isolated from acute infection and expressed in 293T cells. Our results show that both transmitted/founder Envs had similar degrees of glycosylation site occupancy as well as similar glycan profiles. Compared to 293T-derived recombinant Envs from viruses isolated from chronic HIV-1, transmitted/founder Envs displayed marked differences in their glycosylation site occupancies and in their amounts of complex glycans. Our analysis reveals that the glycosylation patterns of transmitted/founder Envs from two different clades (B and C) are more similar to each other than they are to the glycosylation patterns of chronic HIV-1 Envs derived from their own clades.

ChatGPT has enabled access to artificial intelligence (AI)-generated writing for the masses, initiating a culture shift in the way people work, learn, and write. The need to discriminate human writing from AI is now both critical and urgent. Addressing this need, we report a method for discriminating text generated by ChatGPT from (human) academic scientists, relying on prevalent and accessible supervised classification methods. The approach uses new features for discriminating (these) humans from AI; as examples, scientists write long paragraphs and have a penchant for equivocal language, frequently using words like “but,” “however,” and “although.” With a set of 20 features, we built a model that assigns the author, as human or AI, at over 99% accuracy. This strategy could be further adapted and developed by others with basic skills in supervised classification, enabling access to many highly accurate and targeted models for detecting AI usage in academic writing and beyond.