Network medicine-based epistasis detection in complex diseases: ready for quantum computing.

Most heritable diseases are polygenic. To comprehend the underlying genetic architecture, it is crucial to discover the clinically relevant epistatic interactions (EIs) between genomic single nucleotide polymorphisms (SNPs) (1-3). Existing statistical computational methods for EI detection are mostly limited to pairs of SNPs due to the combinatorial explosion of higher-order EIs. With NeEDL (network-based epistasis detection via local search), we leverage network medicine to inform the selection of EIs that are an order of magnitude more statistically significant compared to existing tools and consist, on average, of five SNPs. We further show that this computationally demanding task can be substantially accelerated once quantum computing hardware becomes available. We apply NeEDL to eight different diseases and discover genes (affected by EIs of SNPs) that are partly known to affect the disease, additionally, these results are reproducible across independent cohorts. EIs for these eight diseases can be interactively explored in the Epistasis Disease Atlas (https://epistasis-disease-atlas.com). In summary, NeEDL demonstrates the potential of seamlessly integrated quantum computing techniques to accelerate biomedical research. Our network medicine approach detects higher-order EIs with unprecedented statistical and biological evidence, yielding unique insights into polygenic diseases and providing a basis for the development of improved risk scores and combination therapies.

Network medicine-based epistasis detection in complex diseases: ready for quantum computing.

Most heritable diseases are polygenic. To comprehend the underlying genetic architecture, it is crucial to discover the clinically relevant epistatic interactions (EIs) between genomic single nucleotide polymorphisms (SNPs)1-3. Existing statistical computational methods for EI detection are mostly limited to pairs of SNPs due to the combinatorial explosion of higher-order EIs. With NeEDL (network-based epistasis detection via local search), we leverage network medicine to inform the selection of EIs that are an order of magnitude more statistically significant compared to existing tools and consist, on average, of five SNPs. We further show that this computationally demanding task can be substantially accelerated once quantum computing hardware becomes available. We apply NeEDL to eight different diseases and discover genes (affected by EIs of SNPs) that are partly known to affect the disease, additionally, these results are reproducible across independent cohorts. EIs for these eight diseases can be interactively explored in the Epistasis Disease Atlas (https://epistasis-disease-atlas.com). In summary, NeEDL is the first application that demonstrates the potential of seamlessly integrated quantum computing techniques to accelerate biomedical research. Our network medicine approach detects higher-order EIs with unprecedented statistical and biological evidence, yielding unique insights into polygenic diseases and providing a basis for the development of improved risk scores and combination therapies.

Identification of a novel 5-aminomethyl-2-thiouridine methyltransferase in tRNA modification.

The uridine at the 34th position of tRNA, which is able to base pair with the 3'-end codon on mRNA, is usually modified to influence many aspects of decoding properties during translation. Derivatives of 5-methyluridine (xm5U), which include methylaminomethyl (mnm-) or carboxymethylaminomethyl (cmnm-) groups at C5 of uracil base, are widely conserved at the 34th position of many prokaryotic tRNAs. In Gram-negative bacteria such as Escherichia coli, a bifunctional MnmC is involved in the last two reactions of the biosynthesis of mnm5(s2)U, in which the enzyme first converts cmnm5(s2)U to 5-aminomethyl-(2-thio)uridine (nm5(s2)U) and subsequently installs the methyl group to complete the formation of mnm5(s2)U. Although mnm5s2U has been identified in tRNAs of Gram-positive bacteria and plants as well, their genomes do not contain an mnmC ortholog and the gene(s) responsible for this modification is unknown. We discovered that MnmM, previously known as YtqB, is the methyltransferase that converts nm5s2U to mnm5s2U in Bacillus subtilis through comparative genomics, gene complementation experiments, and in vitro assays. Furthermore, we determined X-ray crystal structures of MnmM complexed with anticodon stem loop of tRNAGln. The structures provide the molecular basis underlying the importance of U33-nm5s2U34-U35 as the key determinant for the specificity of MnmM.

Structural insights into phosphatidylethanolamine formation in bacterial membrane biogenesis.

Phosphatidylethanolamine (PE), a major component of the cellular membrane across all domains of life, is synthesized exclusively by membrane-anchored phosphatidylserine decarboxylase (PSD) in most bacteria. The enzyme undergoes auto-cleavage for activation and utilizes the pyruvoyl moiety to form a Schiff base intermediate with PS to facilitate decarboxylation. However, the structural basis for self-maturation, PS binding, and decarboxylation processes directed by PSD remain unclear. Here, we present X-ray crystal structures of PSD from Escherichia coli, representing an apo form and a PE-bound complex, in which the phospholipid is chemically conjugated to the essential pyruvoyl residue, mimicking the Schiff base intermediate. The high-resolution structures of PE-complexed PSD clearly illustrate extensive hydrophobic interactions with the fatty acyl chains of the phospholipid, providing insights into the broad specificity of the enzyme over a wide range of cellular PS. Furthermore, these structures strongly advocate the unique topology of the enzyme in a lipid bilayer environment, where the enzyme associates with cell membranes in a monotopic fashion via the N-terminal domain composed of three amphipathic helices. Lastly, mutagenesis analyses reveal that E. coli PSD primarily employs D90/D142-H144-S254 to achieve auto-cleavage for the proenzyme maturation, where D90 and D142 act in complementary to each other.