Humans have a 'highly abundant' number of stable proteins that are not all predicted by genetic code

In 1968, the American biochemist and geneticist Marshall Nirenberg and his colleagues won the Nobel Prize in physiology or medicine for their work deciphering how an organism's proteins are directly linked to its genetic code. The science-journalism coverage adds useful context, while the strongest evidential footing still comes from the underlying data, papers or institutional documentation.

It matters because biology becomes more informative when an observed effect begins to look like a mechanism rather than an isolated pattern. The gap between identifying a correlation in biological data and understanding the causal chain that produces it is routinely underestimated, and the history of biomedical research is populated with associations that collapsed when the mechanism was sought and not found. A result that comes with a proposed mechanism, even a partial one, is more useful than a purely descriptive finding because it generates testable predictions that can narrow the hypothesis space. It's in every textbook from high school to college. " This article has been reviewed according to Science X's editorial process and policies. Alyssa Stone/Northeastern University In 1968, the American biochemist and geneticist Marshall Nirenberg and his colleagues won the Nobel Prize in physiology or medicine for their.

New research from Slavov, published in the journal Nature, adds a new chapter to the story. Much of the data was collected from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium, a national project designed to advance understanding of cancer on.

The dataset included both healthy human tissues and samples from individuals with several different types of cancer, including renal, uterine, breast, prostate and various forms. What we found was that other processes contribute a lot to determining protein sequences. " The researchers said they found many of these "new protein products" were more abundant.

Additionally, the proteins they observed have similar characteristics to proteins associated with Parkinson's and Alzheimer's, he said. Shriri Tsour Meria, a Northeastern graduate who co-authored the paper as a doctoral student in Slavov's lab, highlighted that these results challenge assumptions about protein.

The broader interest lies in whether the reported effect points toward a real mechanism and not merely a reproducible but unexplained association. Biology has learned from decades of biomarker failures that correlation, even robust correlation, is not a substitute for mechanistic understanding. A pathway that can be traced from molecular interaction to cellular response to organismal phenotype provides a far stronger foundation for intervention than a statistical association discovered in a large dataset, however well the statistics are done.

It is a very fundamental observation that, if widely confirmed, is going to change textbooks and it's going to have major implications for health and disease," he said. Shira Tsour et al, Alternate RNA decoding results in stable and abundant proteins in mammals, Nature (2026).

Because this item comes through Phys. org Biology as science journalism, it should be treated as contextual reporting rather than primary evidence. Good science reporting can identify why a result matters, connect it to the wider literature and make technical work readable, but the decisive evidence remains in the original paper, dataset, mission release or technical record. That distinction is especially important when a story is later repeated by aggregators, because repetition increases visibility, not evidential strength.

The next step is to test whether the effect repeats across different methods, cell types, model organisms and experimental conditions. Reproducibility is the first test, but mechanistic dissection is the second, and a result that passes both has a substantially better chance of translating into something clinically or biotechnologically useful. The path from a laboratory finding to an applied outcome typically takes a decade or more, and most findings do not complete it; the current result sits at the beginning of that process.

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