Outcomes of Operatively Treated Acute Knee Dislocations

Knee dislocation is a complex and rare injury often presenting in the context of high velocity trauma. The aim of this study is to establish the subjective outcomes of surgically treated knee dislocations. A total of 20 knees dislocations treated by open repair were reviewed. Their progress and outcomes were assessed by using a modified Lysholm score questionnaire. Data was obtained on patient demographics, details of injury, investigation, treatment, rehabilitation, 24 months objective outcome and subjective outcomes. Six patients had a vascular deficit and six had neurological deficits. The median range of motion was 0°-100°. Patients with an initially lower pre-injury level of function were able to return an activity level comparable to their pre-injury status. 22% of competitive athletes retuned to competitive sports. 38% of patients undertaking heavy activity returned to comparable pre-injury level of activity and 67% of patients undertaking moderate level of activity before injury returned to a comparable level after repair. 68% regularly had problems running, 70% problem squatting, 40% swelling and 42% problem with stairs. Most patients however did not have locking of the knee or problems with knees giving way. Patients pain scores decreased over time to an acceptable level. Despite the severity of the injury, majority of patients achieved a satisfactory outcome, although none of the patients reached the same level of function as before the injury. 80% of the patients were satisfied with their outcome. All dissatisfied patients suffered postoperative complications

Systematic and scalable genome-wide essentiality mapping to identify nonessential genes in phages.

Phages are one of the key ecological drivers of microbial community dynamics, function, and evolution. Despite their importance in bacterial ecology and evolutionary processes, phage genes are poorly characterized, hampering their usage in a variety of biotechnological applications. Methods to characterize such genes, even those critical to the phage life cycle, are labor intensive and are generally phage specific. Here, we develop a systematic gene essentiality mapping method scalable to new phage-host combinations that facilitate the identification of nonessential genes. As a proof of concept, we use an arrayed genome-wide CRISPR interference (CRISPRi) assay to map gene essentiality landscape in the canonical coliphages λ and P1. Results from a single panel of CRISPRi probes largely recapitulate the essential gene roster determined from decades of genetic analysis for lambda and provide new insights into essential and nonessential loci in P1. We present evidence of how CRISPRi polarity can lead to false positive gene essentiality assignments and recommend caution towards interpreting CRISPRi data on gene essentiality when applied to less studied phages. Finally, we show that we can engineer phages by inserting DNA barcodes into newly identified inessential regions, which will empower processes of identification, quantification, and tracking of phages in diverse applications

Multicopy suppressor screens reveal convergent evolution of single-gene lysis proteins

Single-strand RNA (ssRNA) Fiersviridae phages cause host lysis with a product of single gene (sgl for single-gene lysis; product Sgl) that induces autolysis. Many different Sgls have been discovered, but the molecular targets of only a few have been identified. In this study, we used a high-throughput genetic screen to uncover genome-wide host suppressors of diverse Sgls. In addition to validating known molecular mechanisms, we discovered that the Sgl of PP7, an ssRNA phage of Pseudomonas aeruginosa, targets MurJ, the flippase responsible for lipid II export, previously shown to be the target of the Sgl of coliphage M. These two Sgls, which are unrelated and predicted to have opposite membrane topology, thus represent a case of convergent evolution. We extended the genetic screens to other uncharacterized Sgls and uncovered a common set of multicopy suppressors, suggesting that these Sgls act by the same or similar mechanism

Multicopy suppressor screens reveal convergent evolution of single-gene lysis proteins

AbstractSingle-strand RNA (ssRNA) Fiersviridae phages cause host lysis with a product of single gene (sgl for single-gene lysis; product Sgl) that induces autolysis. Many different Sgls have been discovered, but the molecular targets of only a few have been identified. In this study, we used a high-throughput genetic screen to uncover genome-wide host suppressors of diverse Sgls. In addition to validating known molecular mechanisms, we discovered that the Sgl of PP7, an ssRNA phage of Pseudomonas aeruginosa, targets MurJ, the flippase responsible for lipid II export, previously shown to be the target of the Sgl of coliphage M. These two Sgls, which are unrelated and predicted to have opposite membrane topology, thus represent a case of convergent evolution. We extended the genetic screens to other uncharacterized Sgls and uncovered a common set of multicopy suppressors, suggesting that these Sgls act by the same or similar mechanism.</jats:p

Genome-wide CRISPRi design and assay format.

Schematic of steps involved in the arrayed CRISPRi knockdown experiments to assess gene essentiality in phage infectivity cycle. Created with BioRender.com</p

Gene essentiality landscape of phage P1.

The genome-wide map of gene essentiality is shown by calculating the EOP as the ratio of plaques appearing on E. coli BW25113 lawn expressing crRNA targeting respective P1 phage genes to plaques appearing on BW25113 lawn expressing a nontargeting crRNA. The EOP estimations were done by carrying out biological replicates and depicted the average EOP of every gene on the P1 phage genome map (Methods). The underlying data for this figure can be found in Table 2 and S1 Data.</p

List of bacterial strains and phages.

Phages are one of the key ecological drivers of microbial community dynamics, function, and evolution. Despite their importance in bacterial ecology and evolutionary processes, phage genes are poorly characterized, hampering their usage in a variety of biotechnological applications. Methods to characterize such genes, even those critical to the phage life cycle, are labor intensive and are generally phage specific. Here, we develop a systematic gene essentiality mapping method scalable to new phage–host combinations that facilitate the identification of nonessential genes. As a proof of concept, we use an arrayed genome-wide CRISPR interference (CRISPRi) assay to map gene essentiality landscape in the canonical coliphages λ and P1. Results from a single panel of CRISPRi probes largely recapitulate the essential gene roster determined from decades of genetic analysis for lambda and provide new insights into essential and nonessential loci in P1. We present evidence of how CRISPRi polarity can lead to false positive gene essentiality assignments and recommend caution towards interpreting CRISPRi data on gene essentiality when applied to less studied phages. Finally, we show that we can engineer phages by inserting DNA barcodes into newly identified inessential regions, which will empower processes of identification, quantification, and tracking of phages in diverse applications.</div

Lambda phage genome CRISPRi oligo designs.

Blue represents genes, red represents primers, and black is the full genome. Outside is on the positive strand, where inside is negative. (TIF)</p

Insertion and quantification of random DNA barcodes on a nonessential genomic location of lambda and P1vir phage.

(a) Schematic of phage engineering approach: Homologous recombination method was used to engineer phages with random barcodes at a nonessential genomic loci, and nuclease active Cas12a-based counterselection was used to enrich engineered phages. Schematic is shown for barcode insertion and counterselection for lambda phage at the red locus and P1 phage at res locus. Created with BioRender.com. (b) Barcode abundance of P1 phage against its PFU/ml estimations in triplicates. (c) Barcode abundance for both barcoded lambda and P1 phages, when mixed at different ratios. Estimations done in triplicates in a pool (Methods). The underlying data for this figure can be found in S1 Data.</p