The functional decline of tomato plants infected by Candidatus Liberbacter solanacearum: an RNA-seq transcriptomic analysis.

Introduction: Candidatus Liberibacter solanacearum (CLso) is a regulated plant pathogen in European and some Asian countries, associated with severe diseases in economically important Apiaceous and Solanaceous crops, including potato, tomato, and carrot. Eleven haplotypes of CLso have been identified based on the difference in rRNA and conserved genes and host and pathogenicity. Although it is pathogenic to a wide range of plants, the mechanisms of plant response and functional decline of host plants are not well defined. This study aims to describe the underlying mechanism of the functional decline of tomato plants infected by CLso by analyzing the transcriptomic response of tomato plants to CLso haplotypes A and B. Methods: Next-generation sequencing (NGS) data were generated from total RNA of tomato plants infected by CLso haplotypes A and B, and uninfected tomato plants, while qPCR analysis was used to validate the in-silico expression analysis. Gene Ontology and KEGG pathways were enriched using differentially expressed genes. Results: Plants infected with CLso haplotype B saw 229 genes upregulated when compared to uninfected plants, while 1,135 were downregulated. Healthy tomato plants and plants infected by haplotype A had similar expression levels, which is consistent with the fact that CLso haplotype A does not show apparent symptoms in tomato plants. Photosynthesis and starch biosynthesis were impaired while starch amylolysis was promoted in plants infected by CLso haplotype B compared with uninfected plants. The changes in pathway gene expression suggest that carbohydrate consumption in infected plants was more extensive than accumulation. In addition, cell-wall-related genes, including steroid biosynthesis pathways, were downregulated in plants infected with CLso haplotype B suggesting a reduction in membrane fluidity, cell signaling, and defense against bacteria. In addition, genes in phenylpropanoid metabolism and DNA replication were generally suppressed by CLso infection, affecting plant growth and defense. Discussion: This study provides insights into plants' defense and functional decline due to pathogenic CLso using whole transcriptome sequencing and qPCR validation. Our results show how tomato plants react in metabolic pathways during the deterioration caused by pathogenic CLso. Understanding the underlying mechanisms can enhance disease control and create opportunities for breeding resistant or tolerant varieties.

Clasnip: a web-based intraspecies classifier and multi-locus sequence typing for pathogenic microorganisms using fragmented sequences.

Bioinformatic approaches for the identification of microorganisms have evolved rapidly, but existing methods are time-consuming, complicated or expensive for massive screening of pathogens and their non-pathogenic relatives. Also, bioinformatic classifiers usually lack automatically generated performance statistics for specific databases. To address this problem, we developed Clasnip (www.clasnip.com), an easy-to-use web-based platform for the classification and similarity evaluation of closely related microorganisms at interspecies and intraspecies levels. Clasnip mainly consists of two modules: database building and sample classification. In database building, labeled nucleotide sequences are mapped to a reference sequence, and then single nucleotide polymorphisms (SNPs) statistics are generated. A probability model of SNPs and classification groups is built using Hidden Markov Models and solved using the maximum likelihood method. Database performance is estimated using three replicates of two-fold cross-validation. Sensitivity (recall), specificity (selectivity), precision, accuracy and other metrics are computed for all samples, training sets, and test sets. In sample classification, Clasnip accepts inputs of genes, short fragments, contigs and even whole genomes. It can report classification probability and a multi-locus sequence typing table for SNPs. The classification performance was tested using short sequences of 16S, 16-23S and 50S rRNA regions for 12 haplotypes of Candidatus Liberibacter solanacearum (CLso), a regulated plant pathogen associated with severe disease in economically important Apiaceous and Solanaceous crops. The program was able to classify CLso samples with even only 1-2 SNPs available, and achieved 97.2%, 98.8% and 100.0% accuracy based on 16S, 16-23S, and 50S rRNA sequences, respectively. In comparison with all existing 12 haplotypes, we proposed that to be classified as a new haplotype, given samples have at least 2 SNPs in the combined region of 16S rRNA (OA2/Lsc2) and 16-23S IGS (Lp Frag 4-1611F/Lp Frag 4-480R) regions, and 2 SNPs in the 50S rplJ/rplL (CL514F/CL514R) regions. Besides, we have included the databases for differentiating Dickeya spp., Pectobacterium spp. and Clavibacter spp. In addition to bacteria, we also tested Clasnip performance on potato virus Y (PVY). 251 PVY genomes were 100% correctly classified into seven groups (PVYC, PVYN, PVYO, PVYNTN, PVYN:O, Poha, and Chile3). In conclusion, Clasnip is a statistically sound and user-friendly bioinformatic application for microorganism classification at the intraspecies level. Clasnip service is freely available at www.clasnip.com.

Atria: an ultra-fast and accurate trimmer for adapter and quality trimming.

With advances in next-generation sequencing, adapters attached to reads and low-quality bases directly and implicitly hinder downstream analysis. For example, they can produce false-positive single nucleotide polymorphisms (SNP), and generate fragmented assemblies. There is a need for a fast trimming algorithm to remove adapters precisely, especially in read tails with relatively low quality. Here, we present Atria, a trimming program that matches the adapters in paired reads and finds possible overlapped regions using a fast and carefully designed byte-based matching algorithm (O (n) time with O (1) space). Atria also implements multi-threading in both sequence processing and file compression and supports single-end reads. Compared with other trimmers, Atria performs favorably in various trimming and runtime benchmarks of both simulated and real data. We also provide a fast and lightweight byte-based matching algorithm, which can be used in various short-sequence matching applications, such as primer search and seed scanning before alignment.

Diffuse reflectance spectroscopy to monitor murine colorectal tumor progression and therapeutic response (Erratum).

The erratum notes a correction to Fig. 5 for the published article.

Diffuse reflectance spectroscopy to monitor murine colorectal tumor progression and therapeutic response.

SIGNIFICANCE: Many studies in colorectal cancer (CRC) use murine ectopic tumor models to determine response to treatment. However, these models do not replicate the tumor microenvironment of CRC. Physiological information of treatment response derived via diffuse reflectance spectroscopy (DRS) from murine primary CRC tumors provide a better understanding for the development of new drugs and dosing strategies in CRC. AIM: Tumor response to chemotherapy in a primary CRC model was quantified via DRS to extract total hemoglobin content (tHb), oxygen saturation (StO2), oxyhemoglobin, and deoxyhemoglobin in tissue. APPROACH: A multimodal DRS and imaging probe (0.78 mm outside diameter) was designed and validated to acquire diffuse spectra longitudinally-via endoscopic guidance-in developing colon tumors under 5-fluoruracil (5-FU) maximum-tolerated (MTD) and metronomic regimens. A filtering algorithm was developed to compensate for positional uncertainty in DRS measurements Results: A maximum increase in StO2 was observed in both MTD and metronomic chemotherapy-treated murine primary CRC tumors at week 4 of neoadjuvant chemotherapy, with 21 ± 6 % and 17 ± 6 % fold changes, respectively. No significant changes were observed in tHb. CONCLUSION: Our study demonstrates the feasibility of DRS to quantify response to treatment in primary CRC models.