TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions

Comparing Early Transcriptomic Responses of 18 Soybean (Glycine max) Genotypes to Iron Stress

Iron deficiency chlorosis (IDC) is an abiotic stress that negatively affects soybean (Glycine max [L.] Merr.) production. Much of our knowledge of IDC stress responses is derived from model plant species. Gene expression, quantitative trait loci (QTL) mapping, and genome-wide association studies (GWAS) performed in soybean suggest that stress response differences exist between model and crop species. Our current understanding of the molecular response to IDC in soybeans is largely derived from gene expression studies using near-isogenic lines differing in iron efficiency. To improve iron efficiency in soybeans and other crops, we need to expand gene expression studies to include the diversity present in germplasm collections. Therefore, we collected 216 purified RNA samples (18 genotypes, two tissue types [leaves and roots], two iron treatments [sufficient and deficient], three replicates) and used RNA sequencing to examine the expression differences of 18 diverse soybean genotypes in response to iron deficiency. We found a rapid response to iron deficiency across genotypes, most responding within 60 min of stress. There was little evidence of an overlap of specific differentially expressed genes, and comparisons of gene ontology terms and transcription factor families suggest the utilization of different pathways in the stress response. These initial findings suggest an untapped genetic potential within the soybean germplasm collection that could be used for the continued improvement of iron efficiency in soybean.

A multi-omic screening approach for the discovery of thermoactive glycoside hydrolases

Next-generation sequencing and computational biology have facilitated the implementation of new combinatorial screening approaches to discover novel enzymes of biotechnological interest. In this study, we describe the successful establishment of a multi-omic approach for the identification of thermostable hydrolase-encoding genes by determination of gene expression levels. We applied this combinatorial approach using an anaerobic enrichment culture from an Azorean hot spring sample grown on green coffee beans as recalcitrant substrate. An in-depth analysis of the microbial community resulted in microorganisms capable of metabolizing the selected substrate, such as the genera Caloramator, Dictyoglomus and Thermoanaerobacter as active and abundant microorganisms. To discover glycoside hydrolases, 90,342 annotated genes were screened for specific reaction types. A total number of 106 genes encoding cellulases (EC 3.2.1.4), beta-glucosidases (EC 3.2.1.21) and endo-1,4-beta-mannosidases (EC 3.2.1.78) were selected. Mapping of RNA-Seq reads to the related metagenome led to expression levels for each gene. Amongst those, 14 genes, encoding glycoside hydrolases, showed highest expression values, and were used for further cloning. Four proteins were biochemically characterized and were identified as thermoactive glycoside hydrolases with a broad substrate range. This work demonstrated that a combinatory omic approach is a suitable strategy identifying unique thermoactive enzymes from environmental samples.

Analysis of QTL DM4.1 for Downy Mildew Resistance in Cucumber Reveals Multiple subQTL: A Novel RLK as Candidate Gene for the Most Important subQTL

One of the biggest problems in cucumber cultivation is cucurbit downy mildew (DM), caused by the obligate biotroph Pseudoperonospora cubensis. Whereas DM in cucumber was previously efficiently controlled by the dm-1 gene from Indian cucumber accession PI 197087, this resistance was broken by new DM strains, prompting the search for novel sources of resistance. A promising source of resistance is the wild cucumber accession PI 197088. It was previously shown that DM resistance in this genotype inherits polygenically. In this paper, we put the focus on one of the QTL, DM4.1 that is located on chromosome 4. QTL DM4.1 was shown to consist of three subQTL: DM4.1.1 affected pathogen-induced necrosis, DM4.1.2 was shown to have an additive effect on sporulation, and DM4.1.3 had a recessive effect on chlorosis as well as an effect on sporulation. Near-isogenic lines (NILs) were produced by introgressing the subQTLs into a susceptible cucumber line (HS279) with good horticultural traits. Transcriptomic analysis revealed that many genes in general, and defense pathway genes in particular, were differentially expressed in NIL DM4.1.1/.2 compared to NIL DM4.1.3 and the susceptible parent HS279. This indicates that the resistance from subQTL DM4.1.1 and/or subQTL DM4.1.2 likely involves defense signaling pathways, whereas resistance due to subQTL DM4.1.3 is more likely to be independent of known defense pathways. Based on fine-mapping data, we identified the RLK gene CsLRK10L2 as a likely candidate for subQTL DM4.1.2, as this gene was found to have a loss-of-function mutation in the susceptible parent HS279, and was strongly upregulated by P. cubensis inoculation in NIL DM4.1.1/.2. Heterologous expression of this gene triggered necrosis, providing further evidence that this gene is indeed causal for subQTL DM4.1.2.

Novel transcriptional responses to heat revealed by turning up the heat at night

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. 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.

Transcriptome Sequencing Approaches to Elucidate Host-Microbe Interactions in Opportunistic Human Fungal Pathogens

Infections caused by opportunistic human fungal pathogens are a source of increasing medical concern, due to their growing incidence, the emergence of novel pathogenic species, and the lack of effective diagnostics tools. Fungal pathogens are phylogenetically diverse, and their virulence mechanisms can differ widely across species. Despite extensive efforts, the molecular bases of virulence in pathogenic fungi and their interactions with the human host remain poorly understood for most species. In this context, next-generation sequencing approaches hold the promise of helping to close this knowledge gap. In particular, high-throughput transcriptome sequencing (RNA-Seq) enables monitoring the transcriptional profile of both host and microbes to elucidate their interactions and discover molecular mechanisms of virulence and host defense. Here, we provide an overview of transcriptome sequencing techniques and approaches, and survey their application in studying the interplay between humans and fungal pathogens. Finally, we discuss novel RNA-Seq approaches in studying host-pathogen interactions and their potential role in advancing the clinical diagnostics of fungal infections.

Sensitizing bacterial cells to antibiotics by shape recovery triggered biofilm dispersion

Microbial biofilms are a leading cause of chronic infections in humans and persistent biofouling in industries due to extremely high-level tolerance of biofilm cells to antimicrobial agents. Eradicating mature biofilms is especially challenging because of the protection of the extracellular matrix and slow growth of biofilm cells. Recently, we reported that established biofilms can be effectively removed (e.g. 99.9% dispersion of 48 h Pseudomonas aeruginosa PAO1 biofilms) by shape memory polymer-based dynamic changes in surface topography. Here, we demonstrate that such biofilm dispersion also sensitizes biofilm cells to conventional antibiotics. For example, shape recovery in the presence of 50 µg/mL tobramycin reduced biofilm cell counts by more than 3 logs (2,479-fold) compared to the static flat control. The observed effects were attributed to the disruption of biofilm structure and increase in cellular activities as evidenced by an 11.8-fold increase in intracellular level of adenosine triphosphate (ATP), and 4.1-fold increase in expression of the rrnB gene in detached cells. These results can help guide the design of new control methods to better combat biofilm associated antibiotic-resistant infections. STATEMENT OF SIGNIFICANCE: Microbial infections are challenging due to high-level antibiotic resistance of biofilm cells. The protection of an extracellular matrix and slow growth of biofilm cells render conventional antibiotics ineffective. Thus, it is important to develop new technologies that can remove mature biofilms and sensitize biofilm cells to antibiotics. Recently, we demonstrated that dynamic change in surface topography can remove 48 h Pseudomonas aeruginosa PAO1 biofilms by 99.9%. In this study, we investigated how shape recovery triggered dispersion affect the physiology of biofilm cells and associated antibiotic susceptibility. These results are helpful for understanding biofilm dispersion and developing more effective control methods.

Impact of Escherichia coli K12 and O18:K1 on human platelets: Differential effects on platelet activation, RNAs and proteins

Blood platelets can interact with bacteria, possibly leading to platelet activation, cytokine and microparticle release and immune signalling. Besides, bacteria can also affect the platelet RNA content. We investigated the impact of non-pathogenic K12 and pathogenic O18:K1 Escherichia (E.) coli strains on platelet activation, RNA expression patterns, and selected proteins. Depending on bacteria concentration, contact of platelets with E. coli K12 lead to an increase of P-selectin (24–51.3%), CD63 (15.9–24.3%), PAC-1 (3.8–14.9%) and bound fibrinogen (22.4–39%) on the surface. E. coli O18:K1 did not affect these markers. Sequencing analysis of total RNA showed that E. coli K12 caused a significant concentration change of 103 spliced mRNAs, of which 74 decreased. For the RNAs of HMBS (logFC = +5.73), ATP2C1 (logFC = −3.13) and LRCH4 (logFC = −4.07) changes were detectable by thromboSeq and Tuxedo pipelines. By Western blot we observed the conversion of HMBS protein from a 47 kDA to 40 kDa product by E. coli K12, O18:K1 and by purified lipopolysaccharide. While ATP2C1 protein was released from platelets, E. coli either reduced the secretion or broke down the released protein making it undetectable by antibodies. Our results demonstrate that different E. coli strains influence activation, RNA and protein levels differently which may affect platelet-bacteria crosstalk.