Salmonella-Induced Filament Formation Is a Dynamic Phenotype Induced by Rapidly Replicating Salmonella enterica Serovar Typhimurium in Epithelial Cells

Salmonella enterica serovar Typhimurium has the fascinating ability to form tubular structures known as Salmonella-induced filaments (Sifs) in host cells. Here, we show that the prevalence of the Sif phenotype in HeLa cells is affected by host cell density, growth, and the multiplicity of infection. Sif formation was observed in cells that displayed rapid intracellular bacterial replication and was found to be dynamic, being maximal 8 to 10 h postinfection and declining thereafter. The virulence factors SpvB and SseJ were found to negatively modulate Sif formation. Our findings demonstrate the complex and dynamic nature of the Sif phenotype

SseJ Deacylase Activity by Salmonella enterica Serovar Typhimurium Promotes Virulence in Mice

Salmonella enterica serovar Typhimurium utilizes a type III secretion system (TTSS) encoded on Salmonella pathogenicity island-2 (SPI2) to promote intracellular replication during infection, but little is known about the molecular function of SPI2-translocated effectors and how they contribute to this process. SseJ is a SPI2 TTSS effector protein that is homologous to enzymes called glycerophospholipid-cholesterol acyltransferases and, following translocation, localizes to the Salmonella-containing vacuole and Salmonella-induced filaments. Full virulence requires SseJ, as sseJ null mutants exhibit decreased replication in cultured cells and host tissues. This work demonstrates that SseJ is an enzyme with deacylase activity in vitro and identifies three active-site residues. Catalytic SseJ mutants display wild-type translocation and subcellular localization but fail to complement the virulence defect of an sseJ null mutant. In contrast to the wild type, SseJ catalytic mutants fail to down regulate Salmonella-induced filament formation and fail to restore the sifA null mutant phenotype of loss of phagosomal membrane to sifA sseJ null double mutants, suggesting that wild-type SseJ modifies the vacuolar membrane. This is the first demonstration of an enzymatic activity for a SPI2 effector protein and provides support for the hypothesis that the deacylation of lipids on the Salmonella-containing vacuole membrane is important to bacterial pathogenesis

The Role of Protein Phosphatase 4 in Regulating Microtubule Severing in the Caenorhabditis elegans Embryo

MEI-1, the catalytic subunit of the Caenorhabditis elegans “katanin” microtubule-severing complex, is required for meiotic spindle formation. However, MEI-1 must be inactivated after the completion of meiosis to allow formation of the first mitotic spindle. Recent work demonstrated that post-meiotic MEI-1 undergoes ubiquitin-dependent degradation mediated by two independent pathways. Here we describe another level of MEI-1 regulation involving the protein phosphatase 4 (PP4) complex. The PP4 R1 regulatory subunit protein phosphatase four regulatory subunit 1 (ppfr-1) was identified in an RNA interference (RNAi) screen for suppressors of a mei-1(gf) allele that is refractory to post-meiotic degradation. RNAi to the PP4 catalytic subunit PPH-4.1 or to the α4 regulatory PPFR-4 also suppressed lethality of ectopic MEI-1. These results suggest that PP4(+) activates MEI-1, and therefore loss of PP4 decreases ectopic MEI-1(gf) activity. PPH-4.1 and MEI-1 co-immunoprecipitate with one another, indicating that the PP4 complex likely regulates MEI-1 activity directly rather than through an intermediate. The ppfr-1 mutant has subtle meiotic defects indicating that PPFR-1 also regulates MEI-1 during meiosis. MBK-2 is the only kinase known to phosphorylate MEI-1 and triggers post-meiotic MEI-1 degradation. However, genetic interactions between PP4 and mbk-2 were not consistent with an antagonistic relationship between the phosphatase and kinase. Additionally, reducing PP4 in mei-1(gf) did not change the level or localization of post-meiotic MEI-1. Thus, by making use of a genetic background where MEI-1 is ectopically expressed, we have uncovered a third mechanism of MEI-1 regulation, one based on phosphorylation but independent of degradation. The redundant regulatory pathways likely contribute in different ways to the rapid and precise post-meiotic inactivation of MEI-1 microtubule-severing activity

Antibacterial autophagy occurs at PtdIns(3)P-enriched domains of the endoplasmic reticulum and requires Rab1 GTPase

Autophagy mediates the degradation of cytoplasmic components in eukaryotic cells and plays a key role in immunity. The mechanism of autophagosome formation is not clear. Here we examined two potential membrane sources for antibacterial autophagy: the ER and mitochondria. DFCP1, a marker of specialized ER domains known as ‘omegasomes,’ associated with Salmonella-containing autophagosomes via its PtdIns(3)P and ER-binding domains, while a mitochondrial marker (cytochrome b5-GFP) did not. Rab1 also localized to autophagosomes, and its activity was required for autophagosome formation, clearance of protein aggregates and peroxisomes, and autophagy of Salmonella. Overexpression of Rab1 enhanced antibacterial autophagy. The role of Rab1 in antibacterial autophagy was independent of its role in ER-to-Golgi transport. Our data suggest that antibacterial autophagy occurs at omegasomes and reveal that the Rab1 GTPase plays a crucial role in mammalian autophagy

Wastewater sequencing reveals early cryptic SARS-CoV-2 variant transmission.

As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing and/or sequencing capacity, which can also introduce biases1-3. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing4,5. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We developed and deployed improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detected emerging variants of concern up to 14 days earlier in wastewater samples, and identified multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission

Wastewater sequencing uncovers early, cryptic SARS-CoV-2 variant transmission

Summary As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing/sequencing capacity, which can also introduce biases. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here, we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We develop and deploy improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detect emerging variants of concern up to 14 days earlier in wastewater samples, and identify multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission