Distinct patterns of mutational sensitivity for λ resistance and maltodextrin transport in Escherichia coli LamB

Prophage maintenance is determined by environment-dependent selective sweeps rather than mutational availability

Prophages, viral sequences integrated into bacterial genomes, can be beneficial and costly. Despite the risk of prophage activation and subsequent bacterial death, active prophages are present in most bacterial genomes. However, our understanding of the selective forces that maintain prophages in bacterial populations is limited. Combining experimental evolution with stochastic modeling, we show that prophage maintenance and loss are primarily determined by environmental conditions that alter the net fitness effect of a prophage on its bacterial host. When prophages are too costly, they are rapidly lost through environment-specific sequences of selective sweeps. Conflicting selection pressures that select against the prophage but for a prophage-encoded accessory gene can maintain prophages. The dynamics of prophage maintenance additionally depend on the sociality of this accessory gene. Prophage-encoded genes that exclusively benefit the lysogen maintain prophages at higher frequencies compared with genes that benefit the entire population. That is because the latter can protect phage-free "cheaters," reducing the benefit of maintaining the prophage. Our simulations suggest that environmental variation plays a larger role than mutation rates in determining prophage maintenance. These findings highlight the complexity of selection pressures that act on mobile genetic elements and challenge our understanding of the role of environmental factors relative to random chance events in shaping the evolutionary trajectory of bacterial populations. By shedding light on the key factors that shape microbial populations in the face of environmental changes, our study significantly advances our understanding of the complex dynamics of microbial evolution and diversification.

ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction

Predicting the effects of mutations in proteins is critical to many applications, from understanding genetic disease to designing novel proteins that can address our most pressing challenges in climate, agriculture and healthcare. Despite a surge in machine learning-based protein models to tackle these questions, an assessment of their respective benefits is challenging due to the use of distinct, often contrived, experimental datasets, and the variable performance of models across different protein families. Addressing these challenges requires scale. To that end we introduce ProteinGym, a large-scale and holistic set of benchmarks specifically designed for protein fitness prediction and design. It encompasses both a broad collection of over 250 standardized deep mutational scanning assays, spanning millions of mutated sequences, as well as curated clinical datasets providing high-quality expert annotations about mutation effects. We devise a robust evaluation framework that combines metrics for both fitness prediction and design, factors in known limitations of the underlying experimental methods, and covers both zero-shot and supervised settings. We report the performance of a diverse set of over 70 high-performing models from various subfields (eg., alignment-based, inverse folding) into a unified benchmark suite. We open source the corresponding codebase, datasets, MSAs, structures, model predictions and develop a user-friendly website that facilitates data access and analysis.

Integrating thousands of PTEN variant activity and abundance measurements reveals variant subgroups and new dominant negatives in cancers

Background

PTEN is a multi-functional tumor suppressor protein regulating cell growth, immune signaling, neuronal function, and genome stability. Experimental characterization can help guide the clinical interpretation of the thousands of germline or somatic PTEN variants observed in patients. Two large-scale mutational datasets, one for PTEN variant intracellular abundance encompassing 4112 missense variants and one for lipid phosphatase activity encompassing 7244 variants, were recently published. The combined information from these datasets can reveal variant-specific phenotypes that may underlie various clinical presentations, but this has not been comprehensively examined, particularly for somatic PTEN variants observed in cancers.

Methods

Here, we add to these efforts by measuring the intracellular abundance of 764 new PTEN variants and refining abundance measurements for 3351 previously studied variants. We use this expanded and refined PTEN abundance dataset to explore the mutational patterns governing PTEN intracellular abundance, and then incorporate the phosphatase activity data to subdivide PTEN variants into four functionally distinct groups.

Results

This analysis revealed a set of highly abundant but lipid phosphatase defective variants that could act in a dominant-negative fashion to suppress PTEN activity. Two of these variants were, indeed, capable of dysregulating Akt signaling in cells harboring a WT PTEN allele. Both variants were observed in multiple breast or uterine tumors, demonstrating the disease relevance of these high abundance, inactive variants.

Conclusions

We show that multidimensional, large-scale variant functional data, when paired with public cancer genomics datasets and follow-up assays, can improve understanding of uncharacterized cancer-associated variants, and provide better insights into how they contribute to oncogenesis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-021-00984-x.

Coevolutionary phage training leads to greater bacterial suppression and delays the evolution of phage resistance

The evolution of antibiotic-resistant bacteria threatens to become the leading cause of worldwide mortality. This crisis has renewed interest in the practice of phage therapy. Yet, bacteria's capacity to evolve resistance may debilitate this therapy as well. To combat the evolution of phage resistance and improve treatment outcomes, many suggest leveraging phages' ability to counter resistance by evolving phages on target hosts before using them in therapy (phage training). We found that in vitro, λtrn, a phage trained for 28 d, suppressed bacteria ∼1,000-fold for three to eight times longer than its untrained ancestor. Prolonged suppression was due to a delay in the evolution of resistance caused by several factors. Mutations that confer resistance to λtrn are ∼100× less common, and while the target bacterium can evolve complete resistance to the untrained phage in a single step, multiple mutations are required to evolve complete resistance to λtrn. Mutations that confer resistance to λtrn are more costly than mutations for untrained phage resistance. Furthermore, when resistance does evolve, λtrn is better able to suppress these forms of resistance. One way that λtrn improved was through recombination with a gene in a defunct prophage in the host genome, which doubled phage fitness. This transfer of information from the host genome is an unexpected but highly efficient mode of training phage. Lastly, we found that many other independently trained λ phages were able to suppress bacterial populations, supporting the important role training could play during phage therapeutic development.

Balance between promiscuity and specificity in phage λ host range

As hosts acquire resistance to viruses, viruses must overcome that resistance to re-establish infectivity, or go extinct. Despite the significant hurdles associated with adapting to a resistant host, viruses are evolutionarily successful and maintain stable coevolutionary relationships with their hosts. To investigate the factors underlying how pathogens adapt to their hosts, we performed a deep mutational scan of the region of the λ tail fiber tip protein that mediates contact with the receptor on λ's host, Escherichia coli. Phages harboring amino acid substitutions were subjected to selection for infectivity on wild type E. coli, revealing a highly restrictive fitness landscape, in which most substitutions completely abrogate function. A subset of positions that are tolerant of mutation in this assay, but diverse over evolutionary time, are associated with host range expansion. Imposing selection for phage infectivity on three λ-resistant hosts, each harboring a different missense mutation in the λ receptor, reveals hundreds of adaptive variants in λ. We distinguish λ variants that confer promiscuity, a general ability to overcome host resistance, from those that drive host-specific infectivity. Both processes may be important in driving adaptation to a novel host.

Diversity and Local Coadaptation of Escherichia coli and Coliphages From Small Ruminants

Bacteriophages are highly specific predators that drive bacterial diversity through coevolution while striking tradeoffs among preserving host populations for long-term exploitation and increasing their virulence, structural stability, or host range. Escherichia coli and other coliform bacteria present in the microbiota of milk and during early ripening of raw milk cheeses have been linked to the production of gas, manifested by the appearance of eyes, and the development of off-flavors; thus, they might cause early blowing and cheese spoilage. Here, we report the characterization of coliphages isolated from manure from small ruminant farms and E. coli strains isolated from goat and sheep raw milk cheese. Additionally, the virulence and host range of locally isolated and laboratory collection phages were determined by comparing the susceptibility of E. coli strains from different sources. In agreement with the high genetic diversity found within the species E. coli, clustering analysis of whole-cell protein revealed a total of 13 distinct profiles but none of the raw milk cheese isolates showed inhibition of growth by reference or water-isolated coliphages. Conversely, 10 newly isolated phages had a broad host range (i.e., able to lyse ≥50% of bacterial hosts tested), thus exhibiting utility for biocontrol and only one cheese-isolated E. coli strain was resistant to all the phages. Whereas there was a high positive correlation between bacterial susceptibility range and lysis intensity, the phages virulence decreased as range increased until reaching a plateau. These results suggest local gene-for-gene coevolution between hosts and phages with selective tradeoffs for both resistance and competitive ability of the bacteria and host-range extension and virulence of the phage populations. Hence, different phage cocktail formulations might be required when devising long-term and short-term biocontrol strategies.