Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time (sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi), illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila species, we identified many putatively non-neutral changes in protein-coding genes, non-coding RNA genes, and cis-regulatory regions. These may prove to underlie differences in the ecology and behaviour of these diverse species.

Engineered metabolic pathways constructed from enzymes heterologous to the production host often suffer from flux imbalances, as they typically lack the regulatory mechanisms characteristic of natural metabolism. In an attempt to increase the effective concentration of each component of a pathway of interest, we built synthetic protein scaffolds that spatially recruit metabolic enzymes in a designable manner. Scaffolds bearing interaction domains from metazoan signaling proteins specifically accrue pathway enzymes tagged with their cognate peptide ligands. The natural modularity of these domains enabled us to optimize the stoichiometry of three mevalonate biosynthetic enzymes recruited to a synthetic complex and thereby achieve 77-fold improvement in product titer with low enzyme expression and reduced metabolic load. One of the same scaffolds was used to triple the yield of glucaric acid, despite high titers (0.5 g/l) without the synthetic complex. These strategies should prove generalizeable to other metabolic pathways and programmable for fine-tuning pathway flux.

SUMMARY Cellular processes often depend on stable physical associations between proteins. Despite recent progress, knowledge of the composition of human protein complexes remains limited. To close this gap, we applied an integrative global proteomic profiling approach, based on chromatographic separation of cultured human cell extracts into more than one thousand biochemical fractions which were subsequently analyzed by quantitative tandem mass spectrometry, to systematically identify a network of 13,993 high-confidence physical interactions among 3,006 stably-associated soluble human proteins. Most of the 622 putative protein complexes we report are linked to core biological processes, and encompass both candidate disease genes and unnanotated proteins to inform on mechanism. Strikingly, whereas larger multi-protein assemblies tend to be more extensively annotated and evolutionarily conserved, human protein complexes with 5 or fewer subunits are far more likely to be functionally un-annotated or restricted to vertebrates, suggesting more recent functional innovations.

Adaptation by natural selection depends on the rates, effects, and interactions of many mutations, making it difficult to determine what proportion of mutations in an evolving lineage are beneficial. We analysed 264 complete genomes from 12 Escherichia coli populations to characterize their dynamics over 50,000 generations. The populations that retained the ancestral mutation rate support a model where most fixed mutations are beneficial, the fraction of beneficial mutations declines as fitness rises, and neutral mutations accumulate at a constant rate. We also compared these populations to mutation-accumulation lines evolved under a bottlenecking regime that minimizes selection. Nonsynonymous mutations, intergenic mutations, insertions, and deletions are overrepresented in the long-term populations, further supporting the inference that most mutations that reached high frequency were favoured by selection. These results illuminate the shifting balance of forces that govern genome evolution in populations adapting to a new environment.

*These authors contributed equally to this work.Adaptation depends on the rates, effects, and interactions of many mutations. We analyzed 264 genomes from 12 Escherichia coli populations to characterize their dynamics over 50,000 generations. The trajectories for genome evolution in populations that retained the ancestral mutation rate fit a model where most fixed mutations are beneficial, the fraction of beneficial mutations declines as fitness rises, and neutral mutations accumulate at a constant rate. We also compared these populations to lines evolved under a mutation--accumulation regime that minimizes selection. Nonsynonymous mutations, intergenic mutations, insertions, and deletions are overrepresented in the long--term populations, supporting the inference that most fixed mutations are favored by selection. These results illuminate the shifting balance of forces that govern genome evolution in populations adapting to a new environment.All rights reserved. No reuse allowed without permission.(which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.