The actin crosslinking domain (ACD) is an actin-specific toxin produced by several pathogens, including life-threatening spp. of Vibrio cholerae, Vibrio vulnificus, and Aeromonas hydrophila. Actin crosslinking by ACD is thought to lead to slow cytoskeleton failure owing to a gradual sequestration of actin in the form of nonfunctional oligomers. Here we found that ACD converted cytoplasmic actin into highly toxic oligomers that potently "poisoned" the ability of major actin assembly proteins, formins, to sustain actin polymerization. Thus, ACD can target the most abundant cellular protein by employing actin oligomers as secondary toxins to efficiently subvert cellular functions of actin while functioning at very low doses. Author Manuscript Author ManuscriptAuthor Manuscript Author ManuscriptBacterial toxins are the deadliest compounds on the planet. As little as a single molecule of a delivered toxin can compromise vital functions or even kill an affected host cell (1, 2). This is achieved by amplification of a toxin enzymatic activity via signaling cascades (e.g. by cholera, pertussis, and anthrax toxins) or via enzymatic inhibition of vital host complexes present in relatively few copies (e.g. Shiga and diphtheria toxins acting on ribosomes). Such efficiency is crucial because i) the amount of a toxin produced early upon infection is limited by an initially small number of bacterial cells; ii) the host is protected by commensal bacteria; and iii) the host immune system efficiently neutralizes toxins by means of adaptive (antibodies) and innate (e.g. defensins) (3) humoral defense factors.Owing to its importance in multiple cellular processes, actin is a common target for bacterium-and parasite-produced toxins. Upon delivery to the cytoplasm of host cells via Type I (as part of MARTX toxin) (4) or Type VI (within VgrG1 toxin) (5) secretion systems, the actin crosslinking domain toxin (ACD) catalyzes the covalent crosslinking of K50 in subdomain 2 of one actin monomer with E270 in subdomain 3 of another actin monomer via an amide bond, resulting in the formation of actin oligomers (6, 7). The actin subunits in the oligomers are oriented similar to short-pitch subunits in the filament, except that a major twist of the subdomain-2, required to accommodate such orientation, disrupts the normal inter-subunit interface and precludes polymerization (6).The currently accepted mechanism of ACD toxicity, via sequestering of bulk amounts of actin as non-functional oligomers, is compromised owing to the high concentration (hundreds of micromolar) of actin in a typical animal cell. Extrapolation of in vitro determined rates of the ACD activity (7) to cellular conditions suggests that a single ACD molecule per cell (i.e. ~ 1 pM) would require over six months to covalently crosslink half of all cytoplasmic actin.In contrast to these estimations, the integrity of the intestinal cell monolayers was disrupted when only a small fraction of cellular actin (2-6%) was crosslinked by ACD ( Fig. 1A-C; fig. S1). To account fo...

Background Out of the many pathogenic bacterial species that are known, only a fraction are readily identifiable directly from a complex microbial community using standard next generation DNA sequencing. Long-read sequencing offers the potential to identify a wider range of species and to differentiate between strains within a species, but attaining sufficient accuracy in complex metagenomes remains a challenge. Methods Here, we describe and analytically validate LoopSeq, a commercially available synthetic long-read (SLR) sequencing technology that generates highly accurate long reads from standard short reads. Results LoopSeq reads are sufficiently long and accurate to identify microbial genes and species directly from complex samples. LoopSeq perfectly recovered the full diversity of 16S rRNA genes from known strains in a synthetic microbial community. Full-length LoopSeq reads had a per-base error rate of 0.005%, which exceeds the accuracy reported for other long-read sequencing technologies. 18S-ITS and genomic sequencing of fungal and bacterial isolates confirmed that LoopSeq sequencing maintains that accuracy for reads up to 6 kb in length. LoopSeq full-length 16S rRNA reads could accurately classify organisms down to the species level in rinsate from retail meat samples, and could differentiate strains within species identified by the CDC as potential foodborne pathogens. Conclusions The order-of-magnitude improvement in length and accuracy over standard Illumina amplicon sequencing achieved with LoopSeq enables accurate species-level and strain identification from complex- to low-biomass microbiome samples. The ability to generate accurate and long microbiome sequencing reads using standard short read sequencers will accelerate the building of quality microbial sequence databases and removes a significant hurdle on the path to precision microbial genomics.

Key message The circadian clock controls many molecular activities, impacting experimental interpretation. We quantify the genome-wide effects of time-of-day on the heat-shock response and the effects of “diurnal bias” in stress experiments. Abstract Heat stress has significant adverse effects on plant productivity worldwide. Most experiments examining heat stress are performed during daytime hours, generating a ‘diurnal bias’ in the pathways and regulatory mechanisms identified. Such bias may confound downstream interpretations and limit our understanding of the full response to heat stress. Here we show that the transcriptional and physiological responses to a sudden heat shock in Arabidopsis are profoundly sensitive to the time of day. We observe that plant tolerance and acclimation to heat shock vary throughout the day and are maximal at dusk. Consistently, over 75% of heat-responsive transcripts show a time of day-dependent response, including many previously characterized heat-response genes. This temporal sensitivity implies a complex interaction between time and temperature where daily variations in basal transcription influence thermotolerance. When we examined these transcriptional responses, we uncovered novel night-response genes and cis -regulatory elements, underpinning new aspects of heat stress responses not previously appreciated. Exploiting this temporal variation can be applied to most environmental responses to understand the underlying network wiring. Therefore, we propose that using time as a perturbagen is an approach that will enhance our understanding of plant regulatory networks and responses to environmental stresses. Electronic supplementary material The online version of this article (10.1007/s11103-019-00873-3) contains supplementary material, which is available to authorized users.

In rice, a small increase in nighttime temperature reduces grain yield and quality. How warm nighttime temperatures (WNT) produce these detrimental effects is not well understood, especially in field conditions where the typical day-to-night temperature fluctuation exceeds the mild increase in nighttime temperature. We observed genome-wide disruption of gene expression timing during the reproductive phase in field-grown rice panicles acclimated to 2 to 3 °C WNT. Transcripts previously identified as rhythmically expressed with a 24-h period and circadian-regulated transcripts were more sensitive to WNT than were nonrhythmic transcripts. The system-wide perturbations in transcript levels suggest that WNT disrupt the tight temporal coordination between internal molecular events and the environment, resulting in reduced productivity. We identified transcriptional regulators whose predicted targets are enriched for sensitivity to WNT. The affected transcripts and candidate regulators identified through our network analysis explain molecular mechanisms driving sensitivity to WNT and identify candidates that can be targeted to enhance tolerance to WNT.

AbstractOut of the many pathogenic bacterial species that are known, only a fraction are readily identifiable directly from a complex microbial community using standard next generation DNA sequencing technology. Long-read sequencing offers the potential to identify a wider range of species and to differentiate between strains within a species, but attaining sufficient accuracy in complex metagenomes remains a challenge. Here, we describe and analytically validate LoopSeq, a commercially-available synthetic long-read (SLR) sequencing technology that generates highly-accurate long reads from standard short reads. LoopSeq reads are sufficiently long and accurate to identify microbial genes and species directly from complex samples. LoopSeq applied to full-length 16S rRNA genes from known strains in a microbial community perfectly recovered the full diversity of full-length exact sequence variants in a known microbial community. Full-length LoopSeq reads had a per-base error rate of 0.005%, which exceeds the accuracy reported for other long-read sequencing technologies. 18S-ITS and genomic sequencing of fungal and bacterial isolates confirmed that LoopSeq sequencing maintains that accuracy for reads up to 6 kilobases in length. Analysis of rinsate from retail meat samples demonstrated that LoopSeq full-length 16S rRNA synthetic long-reads could accurately classify organisms down to the species level, and could differentiate between different strains within species identified by the CDC as potential foodborne pathogens. The order-of-magnitude improvement in both length and accuracy over standard Illumina amplicon sequencing achieved with LoopSeq enables accurate species-level and strain identification from complex and low-biomass microbiome samples. The ability to generate accurate and long microbiome sequencing reads using standard short read sequencers will accelerate the building of quality microbial sequence databases and removes a significant hurdle on the path to precision microbial genomics.

33In rice, a small increase in nighttime temperatures reduces grain yield and quality. How warm nighttime 34 temperatures (WNT) produce these detrimental effects is not well understood, especially in field conditions 35 where the normal day to night temperature fluctuation exceeds the mild increase in nighttime temperature. 36We observed genome-wide disruption of gene expression timing during the reproductive phase on field-37 grown rice panicles acclimated to 2-3°C WNT. Rhythmically expressed transcripts were more sensitive to 38 WNT than non-rhythmic transcripts. The system-wide transcriptional perturbations suggest that WNT 39 disrupts the tight temporal coordination between internal molecular events and the environment resulting 40 in reduced productivity. We identified transcriptional regulators whose predicted targets are enriched for 41 sensitivity to WNT. The affected transcripts and candidate regulators identified through our network 42 analysis explain molecular mechanisms driving sensitivity to WNT and candidates that can be targeted to 43 enhance tolerance to WNT. 44 45 KEYWORDS: climate change impact, global food security, nighttime temperature increase, circadian 46 regulators, diel transcriptional networks, rhythmic expression, rice panicles 47 48 49 101 102 RESULTS 103 WNT NEGATIVELY IMPACT BIOMASS AND YIELD 104 105IR64, a popular high-yielding rice variety, was grown under normal nighttime temperatures (NNT) or under 106 warm nighttime temperatures (WNT), using a field-based infrared ceramic heating system (Fig. S1). WNT 107 treatment started at panicle initiation and continued through maturity. At 50% flowering, field-grown rice 108 panicles were collected for transcriptional analysis throughout the 24h cycle. WNT maintained a 2-3°C

The resolution of variation within species is critical for interpreting and acting on many microbial measurements. In the key foodborne pathogens Escherichia coli and Salmonella, the primary sub-species classification scheme used is serotyping: differentiating variants within these species by surface antigen profiles. Serotype prediction from whole-genome sequencing (WGS) of isolates is now seen as comparable or preferable to traditional laboratory methods where WGS is available. However, laboratory and WGS methods depend on an isolation step that is time-consuming and incompletely represents the sample when multiple strains are present. Community sequencing approaches that skip the isolation step are therefore of interest for pathogen surveillance. Here we evaluated the viability of amplicon sequencing of the full-length 16S rRNA gene for serotyping S. enterica and E. coli. We developed a novel algorithm for serotype prediction, implemented as an R package (Seroplacer), which takes as input full-length 16S rRNA gene sequences and outputs serovar predictions after phylogenetic placement into a reference phylogeny. We achieved over 89% accuracy in predicting Salmonella serotypes on in silico test data, and identified key pathogenic serovars of Salmonella and E. coli in isolate and environmental test samples. Although serotype prediction from 16S sequences is not as accurate as serotype prediction from WGS of isolates, the potential to identify dangerous serovars directly from amplicon sequencing of environmental samples is intriguing for pathogen surveillance. The capabilities developed here are also broadly relevant to other applications where intra-species variation and direct sequencing from environmental samples could be valuable.