Optimizing the strain engineering process for industrial-scale production of bio-based molecules.

Biomanufacturing could contribute as much as ${\$}$30 trillion to the global economy by 2030. However, the success of the growing bioeconomy depends on our ability to manufacture high-performing strains in a time- and cost-effective manner. The Design-Build-Test-Learn (DBTL) framework has proven to be an effective strain engineering approach.

Deep mutational scanning of essential bacterial proteins can guide antibiotic development.

Deep mutational scanning is a powerful approach to investigate a wide variety of research questions including protein function and stability. Here, we perform deep mutational scanning on three essential E. coli proteins (FabZ, LpxC and MurA) involved in cell envelope synthesis using high-throughput CRISPR genome editing, and study the effect of the mutations in their original genomic context.

Basic protein sequence analysis.

Prediction of molecular function of proteins has become an important task in the genomics era. A wide variety of sequence analysis tools are available to biologists for this task. We have selected one or two primary protocols for tasks such as domain detection, subcellular localization, and motif detection.

Phylogenomic inference of protein molecular function.

With the explosion in sequence data, accurate prediction of protein function has become a vital task in prioritizing experimental investigation. While computationally efficient methods for homology-based function prediction have been developed to make this approach feasible in high-throughput mode, it is not without its dangers. Biological processes such as gene duplication, domain shuffling, and speciation produce families of related genes whose gene products can have vastly different molecular functions.

Basic protein sequence analysis.

Prediction of molecular function of proteins has become an important task in the genomics era. A wide variety of sequence analysis tools are available to biologists for this task. We have selected one or two primary protocols for tasks such as domain detection, subcellular localization, and motif detection.

The Generation Challenge Programme comparative plant stress-responsive gene catalogue.

The Generation Challenge Programme (GCP; www.generationcp.org) has developed an online resource documenting stress-responsive genes comparatively across plant species.

Automated protein subfamily identification and classification.

Function prediction by homology is widely used to provide preliminary functional annotations for genes for which experimental evidence of function is unavailable or limited. This approach has been shown to be prone to systematic error, including percolation of annotation errors through sequence databases. Phylogenomic analysis avoids these errors in function prediction but has been difficult to automate for high-throughput application.

Berkeley Phylogenomics Group web servers: resources for structural phylogenomic analysis.

Phylogenomic analysis addresses the limitations of function prediction based on annotation transfer, and has been shown to enable the highest accuracy in prediction of protein molecular function. The Berkeley Phylogenomics Group provides a series of web servers for phylogenomic analysis: classification of sequences to pre-computed families and subfamilies using the PhyloFacts Phylogenomic Encyclopedia, FlowerPower clustering of proteins sharing the same domain architecture, MUSCLE multiple sequence alignment, SATCHMO simultaneous alignment and tree construction and SCI-PHY subfamily identification. The PhyloBuilder web server provides an integrated phylogenomic pipeline starting with a user-supplied protein sequence, proceeding to homolog identification, multiple alignment, phylogenetic tree construction, subfamily identification and structure prediction.

FlowerPower: clustering proteins into domain architecture classes for phylogenomic inference of protein function.

Background: Function prediction by transfer of annotation from the top database hit in a homology search has been shown to be prone to systematic error. Phylogenomic analysis reduces these errors by inferring protein function within the evolutionary context of the entire family. However, accuracy of function prediction for multi-domain proteins depends on all members having the same overall domain structure.

PhyloFacts: an online structural phylogenomic encyclopedia for protein functional and structural classification.

The Berkeley Phylogenomics Group presents PhyloFacts, a structural phylogenomic encyclopedia containing almost 10,000 'books' for protein families and domains, with pre-calculated structural, functional and evolutionary analyses. PhyloFacts enables biologists to avoid the systematic errors associated with function prediction by homology through the integration of a variety of experimental data and bioinformatics methods in an evolutionary framework. Users can submit sequences for classification to families and functional subfamilies.

Phylogenomic analysis of the receptor-like proteins of rice and Arabidopsis.

The tomato (Lycopersicon esculentum) Cf-9 resistance gene encodes the first characterized member of the plant receptor-like protein (RLP) family. Other RLPs such as CLAVATA2 and TOO MANY MOUTHS are known to regulate development. The domain structure of RLPs consists of extracellular leucine-rich repeats, a transmembrane helix, and a short cytoplasmic region.

Proteome analysis of the rice etioplast: metabolic and regulatory networks and novel protein functions.

We report an extensive proteome analysis of rice etioplasts, which were highly purified from dark-grown leaves by a novel protocol using Nycodenz density gradient centrifugation. Comparative protein profiling of different cell compartments from leaf tissue demonstrated the purity of the etioplast preparation by the absence of diagnostic marker proteins of other cell compartments. Systematic analysis of the etioplast proteome identified 240 unique proteins that provide new insights into heterotrophic plant metabolism and control of gene expression.

Subfamily hmms in functional genomics.

The limitations of homology-based methods for prediction of protein molecular function are well known; differences in domain structure, gene duplication events and errors in existing database annotations complicate this process. In this paper we present a method to detect and model protein subfamilies, which can be used in high-throughput, genome-scale phylogenomic inference of protein function. We demonstrate the method on a set of nine PFAM families, and show that subfamily HMMs provide greater separation of homologs and non-homologs than is possible with a single HMM for each family.

Molecular characterization of proteolytic cleavage sites of the Pseudomonas syringae effector AvrRpt2.

During infection of Arabidopsis thaliana, the bacterium Pseudomonas syringae pv tomato delivers the effector protein AvrRpt2 into the plant cell cytosol. Within the plant cell, AvrRpt2 undergoes N-terminal processing and causes elimination of Arabidopsis RIN4. Previous work established that AvrRpt2 is a putative cysteine protease, and AvrRpt2 processing and RIN4 elimination require an intact predicted catalytic triad in that AvrRpt2.

Predicted hexameric structure of the Agrobacterium VirB4 C terminus suggests VirB4 acts as a docking site during type IV secretion.

The Agrobacterium T-DNA transporter belongs to a growing class of evolutionarily conserved transporters, called type IV secretion systems (T4SSs). VirB4, 789 aa, is the largest T4SS component, providing a rich source of possible structural domains. Here, we use a variety of bioinformatics methods to predict that the C-terminal domain of VirB4 (including the Walker A and B nucleotide-binding motifs) is related by divergent evolution to the cytoplasmic domain of TrwB, the coupling protein required for conjugative transfer of plasmid R388 from Escherichia coli.