Barbara J. May 2026-11-05
Barbara J. May is the first author of a 2001 whole-genome sequencing study of Pasteurella multocida strain Pm70. The team assembled its DNA sequence and identified predicted coding sequences, providing a reference for investigating a bacterial pathogen rather than treating all strains as genetically identical.[ref]
The work also used DNA microarrays to compare gene expression under ordinary and iron-depleted conditions. This connected the sequence catalogue with a physiological perturbation: which measured expression patterns changed when an important nutrient became less available?[ref]
Prediction and functional demonstration remain different steps. A sequence resembling a transport protein suggests a possible role; an expression change adds evidence of regulation, while directly testing transport or removing the gene asks a further question. The genome resource made such hypotheses more specific without validating every predicted function at once.
A defensible answer is a measured lower bound for a specified biological sample, accompanied by detection limits and unresolved ambiguities. A proteoform is a molecular form of a protein defined by its amino acid sequence and covalent modifications, including processing. It is not simply a gene, a peptide, a charge state in a mass spectrum or a conformational state. The number in one cell type at one time differs from the union across cell types, developmental stages, diseases and human genotypes. Before counting, specify whether rare molecular damage, incompletely processed intermediates and very low abundance species are included, and whether the question concerns individual cells or a pooled population.
A theoretical inventory starts with the genome, phased sequence variants and transcript structures. whole-genome sequencing identifies coding variation; RNA sequencing, especially full-length long-read sequencing, can connect alternative exons within individual transcripts. ribosome profiling supplies evidence that candidate reading frames are translated. However, an RNA isoform is not proof of a stable protein, and none of these methods alone establishes the combination of post-translational modifications on the mature chain. A schematic upper bound is
where indexes distinct sequence forms and site permits an unmodified state plus mutually exclusive modified states. This assumes independence between sites and that every combination is realizable. Steric constraints, processing, mutually exclusive pathways and low occupancy invalidate that assumption in real cells. Multiplying all documented sites therefore estimates a possible space, not the number that exists.
bottom-up proteomics provides a broad experimental survey. Extract proteins under conditions that minimize proteolysis and preserve labile modifications; fractionate, digest with complementary proteases, and analyse peptides by liquid chromatography-mass spectrometry and tandem mass spectrometry. Search against a sample-specific sequence database and relevant modification hypotheses, then validate sites with diagnostic fragments and, where needed, synthetic standards. Modification-specific enrichment increases sensitivity but changes the sampled population and cannot supply an unbiased count by itself. Control peptide- and protein-level false discovery rates, distinguish unique from shared peptides, and report ambiguously localized modifications explicitly. Enlarging a search to every possible modification greatly increases the chance of a convincing but incorrect match.
The central limitation is loss of linkage. Suppose sites A and B occur on different digestion products. A mixture containing equal amounts of unmodified and doubly modified chains gives 50% modification at each site. A different mixture containing equal amounts of A-only and B-only chains gives exactly the same site occupancies, but contains different intact forms. No amount of more precise measurement of these two isolated peptides distinguishes the populations. A spanning peptide, a larger linked fragment or intact-chain evidence is required.
Figure 1.
Different intact proteoform populations can give identical modification frequencies after digestion
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top-down proteomics addresses this by separating and measuring intact proteins before fragmenting their selected ions. High-resolution intact mass constrains the total composition, while sequence fragments connect modifications to the same molecule and localize them. Electron-based fragmentation can help retain modifications lost during energetic fragmentation. middle-down proteomics uses larger fragments to recover partial linkage when complete intact-chain characterization is difficult. John C. Tran and colleagues demonstrated discovery-scale intact-protein analysis, illustrating that sequence variants and modification patterns can be mapped together rather than reconstructed solely from disconnected peptides.[ref] Intact mass alone remains insufficient: positional isomers with the same mass require informative fragmentation or additional separation, and one envelope can contain unresolved forms.
A practical programme would combine these measurements across well-defined human cell populations, using biological replicates, standardized handling and a documented range of physiological perturbations. It would use sequence-resolved RNA data to constrain searches, broad bottom-up data to locate promising variation, and targeted top-down or middle-down analysis to establish co-occurrence. Spike-in proteins spanning abundances and sizes would measure extraction loss and detection sensitivity. Time courses, immediate protein denaturation, protease and phosphatase inhibition, and processing blanks would help distinguish cellular modification from oxidation, protein deamidation or cleavage during preparation. Very large, hydrophobic and scarce proteins require specific extraction and separation strategies; their absence from a spectrum cannot be treated as biological absence.
Bulk and single-cell measurements answer different questions. A bulk sample may show two proteoforms expressed in different cells; it does not show that both occur in each cell. Conversely, detecting two modifications in one cell does not demonstrate that they occupy the same protein molecule. Single-cell sensitivity and molecular linkage must therefore be evaluated separately. Quantitative standards and targeted follow-up can establish whether a new low-abundance assignment is reproducible rather than a one-off incorrect match.
Finally, merge identifications by molecular identity rather than by peptide count, search-engine entry or ion charge. Record fully characterized forms separately from groups sharing an unresolved mass or site pattern, and control identification error at the proteoform level. Plot discovery against sampling depth, tissues and perturbations; any extrapolation to unseen forms requires explicit assumptions about abundance and sampling heterogeneity. Sequence prediction supplies candidates, peptide analysis supplies coverage, and intact or linked-fragment evidence establishes combinations. A universal exact count cannot be inferred by multiplying modification sites or summing database entries.
Pradeep Reddy Marri 2026-11-05
Pradeep Reddy Marri led a comparative whole-genome sequencing study of commensal and pathogenic Neisseria. The 2010 paper found that commensal species carry many virulence alleles and have extensive genetic exchange with other Neisseria. A harmless colonizer can therefore be a reservoir of genetic variants relevant to a pathogenic relative.[ref]
This connects horizontal gene transfer to the evolution of disease-associated traits. Possessing a particular allele does not by itself establish pathogenicity: its genomic context, regulation and host interaction also matter.
Whole-genome sequencing Created 2026-10-20 Updated 2026-11-05
Whole-genome sequencing aims to sample sequence across an entire genome, rather than a selected panel or expressed subset. The label describes intended scope, not guaranteed complete observation of every base. Repeats, uneven representation and insufficient sequencing depth can leave regions unresolved. Analysis can involve mapping to a reference or genome assembly, and variants absent from the reference can require special attention. [ref]