Revisiting the Trans-Sacral Approach for Large Rectal Adenomas, Surgical Technique, and Oncological Outcome: a Case Series.

The standard oncologic surgeries for rectal carcinoma are radical trans abdominal procedures, However, these radical procedures are not suitable for large rectal adenomas. The transsacral approach for rectal adenoma was first described by Kraske and since then it has been utilized for various benign conditions of low and mid-rectum as well as for certain cancers. We are presenting a series of 5 consecutive cases of trans-sacral resection done in the past 7 years between January, 2016, until June, 2023, at the Department of Surgical Oncology, Cancer Research Institute, HIMS Dehradun, for large mid- and lower rectal adenoma. There were 5 patients who underwent transsacral excision of rectal adenoma. Three patients were male and 2 were female. All the patients underwent surgery after confirming the diagnosis of adenoma and metastatic work up. The postoperative histopathological examination showed adenocarcinoma infiltrating submucosa (T1) in one patient; however, other 4 patients had adenoma reconfirmed. The transsacral approach may not be the method of choice for the rectal carcinoma but it is a very useful surgical alternative to the large rectal adenoma where there is no invasive component and which cannot be managed by any other methods.

UltraSEQ, a Universal Bioinformatic Platform for Information-Based Clinical Metagenomics and Beyond.

Applied metagenomics is a powerful emerging capability enabling the untargeted detection of pathogens, and its application in clinical diagnostics promises to alleviate the limitations of current targeted assays. While metagenomics offers a hypothesis-free approach to identify any pathogen, including unculturable and potentially novel pathogens, its application in clinical diagnostics has so far been limited by workflow-specific requirements, computational constraints, and lengthy expert review requirements. To address these challenges, we developed UltraSEQ, a first-of-its-kind accurate and scalable metagenomic bioinformatic tool for potential clinical diagnostics and biosurveillance utility. Here, we present the results of the evaluation of our novel UltraSEQ pipeline using an in silico-synthesized metagenome, mock microbial community data sets, and publicly available clinical data sets from samples of different infection types, including both short-read and long-read sequencing data. Our results show that UltraSEQ successfully detected all expected species across the tree of life in the in silico sample and detected all 10 bacterial and fungal species in the mock microbial community data set. For clinical data sets, even without requiring data set-specific configuration setting changes, background sample subtraction, or prior sample information, UltraSEQ achieved an overall accuracy of 91%. Furthermore, as an initial demonstration with a limited patient sample set, we show UltraSEQ's ability to provide antibiotic resistance and virulence factor genotypes that are consistent with phenotypic results. Taken together, the above-described results demonstrate that the UltraSEQ platform offers a transformative approach for microbial and metagenomic sample characterization, employing a biologically informed detection logic, deep metadata, and a flexible system architecture for the classification and characterization of taxonomic origin, gene function, and user-defined functions, including disease-causing infections. IMPORTANCE Traditional clinical microbiology-based diagnostic tests rely on targeted methods that can detect only one to a few preselected organisms or slow, culture-based methods. Although widely used today, these methods have several limitations, resulting in rates of cases of an unknown etiology of infection of >50% for several disease types. Massive developments in sequencing technologies have made it possible to apply metagenomic methods to clinical diagnostics, but current offerings are limited to a specific disease type or sequencer workflow and/or require laboratory-specific controls. The limitations associated with current clinical metagenomic offerings result from the fact that the backend bioinformatic pipelines are optimized for the specific parameters described above, resulting in an excess of unmaintained, redundant, and niche tools that lack standardization and explainable outputs. In this paper, we demonstrate that UltraSEQ uses a novel, information-based approach that enables accurate, evidence-based predictions for diagnosis as well as the functional characterization of a sample.

Analysis of metatranscriptomic methods to enable wastewater-based biosurveillance of all infectious diseases.

Introduction: Wastewater-based surveillance emerged during the COVID-19 pandemic as an efficient way to quickly screen large populations, monitor infectious disease transmission over time, and identify whether more virulent strains are becoming more prevalent in the region without burdening the health care system with individualized testing. Ohio was one of the first states to implement wastewater monitoring through its Ohio Coronavirus Wastewater Monitoring Network (OCWMN), originally tracking the prevalence of COVID-19 by quantitative qPCR from over 67 sites across the state. The OCWMN evolved along with the pandemic to include sequencing the SARS-CoV-2 genome to assess variants of concern circulating within the population. As the pandemic wanes, networks such as OCWMN can be expanded to monitor other infectious diseases and outbreaks of interest to the health department to reduce the burden of communicable diseases. However, most surveillance still utilizes qPCR based diagnostic tests for individual pathogens, which is hard to scale for surveillance of multiple pathogens. Methods: Here we have tested several genomic methods, both targeted and untargeted, for wastewater-based biosurveillance to find the most efficient procedure to detect and track trends in reportable infectious diseases and outbreaks of known pathogens as well as potentially novel pathogens or variants on the rise in our communities. RNA extracts from the OCWMN were provided weekly from 10 sites for 6 weeks. Total RNA was sequenced from the samples on the Illumina NextSeq and on the MinION to identify pathogens present. The MinION long read platform was also used to sequence SARS-CoV-2 with the goal of reducing the complexity of variant calling in mixed populations as occurs with short Illumina reads. Finally, a targeted hybridization approach was tested for compatibility with wastewater RNA samples. Results and discussion: The data analyzed here provides a baseline assessment that demonstrates that wastewater is a rich resource for infectious disease epidemiology and identifies technology gaps and potential solutions to enable this resource to be used by public health laboratories to monitor the infectious disease landscape of the regions they serve.

Function-based classification of hazardous biological sequences: Demonstration of a new paradigm for biohazard assessments.

Bioengineering applies analytical and engineering principles to identify functional biological building blocks for biotechnology applications. While these building blocks are leveraged to improve the human condition, the lack of simplistic, machine-readable definition of biohazards at the function level is creating a gap for biosafety practices. More specifically, traditional safety practices focus on the biohazards of known pathogens at the organism-level and may not accurately consider novel biodesigns with engineered functionalities at the genetic component-level. This gap is motivating the need for a paradigm shift from organism-centric procedures to function-centric biohazard identification and classification practices. To address this challenge, we present a novel methodology for classifying biohazards at the individual sequence level, which we then compiled to distinguish the biohazardous property of pathogenicity at the whole genome level. Our methodology is rooted in compilation of hazardous functions, defined as a set of sequences and associated metadata that describe coarse-level functions associated with pathogens (e.g., adherence, immune subversion). We demonstrate that the resulting database can be used to develop hazardous "fingerprints" based on the functional metadata categories. We verified that these hazardous functions are found at higher levels in pathogens compared to non-pathogens, and hierarchical clustering of the fingerprints can distinguish between these two groups. The methodology presented here defines the hazardous functions associated with bioengineering functional building blocks at the sequence level, which provide a foundational framework for classifying biological hazards at the organism level, thus leading to the improvement and standardization of current biosecurity and biosafety practices.

Strain-Level Profiling of Oral Microbiota with Targeted Sequencing.

Targeted sequencing of one or more regions of the bacterial 16S rRNA gene fragment has emerged as a gold standard for investigating taxonomic diversity in complex microbial communities, such as those found in the oral cavity. While this approach is useful for identifying bacteria up to genus level, its ability to distinguish between many closely related oral species, or explore strain-level variations within each species, is very limited. Here we present an approach based on targeted sequencing the 16S-23S Intergenic Spacer Region (ISR) in the bacterial ribosomal operon for taxonomic characterization of microbial communities at a subspecies or strain level. This approach retains the advantages of 16S-based methods, such as easy library preparation, high throughput, short amplicon sizes, and low cost of sequencing, while providing subspecies-level resolution as a result of naturally higher genetic diversity present in the ISR compared to the 16S hypervariable regions. These advantages make it an excellent tool for high-resolution oral microbiota characterization.

Effect of HIV/HAART and Other Clinical Variables on the Oral Mycobiome Using Multivariate Analyses.

The oral microbiome is considered an important factor in health and disease. We recently reported significant effects of HIV and several other clinical variables on the oral bacterial communities in a large cohort of HIV-positive and -negative individuals. The purpose of the present study was to similarly analyze the oral mycobiome in the same cohort. To identify fungi, the internal transcribed spacer 2 (ITS2) of the fungal rRNA genes was sequenced using oral rinse samples from 149 HIV-positive and 88 HIV-negative subjects that had previously undergone bacterial amplicon sequencing. Quantitative PCR was performed for total fungal content and total bacterial content. Interestingly, samples often showed predominance of a single fungal species with four major clusters predominated by Candida albicans, Candida dubliniensis, Malassezia restricta, or Saccharomyces cerevisiae Quantitative PCR analysis showed the Candida-dominated sample clusters had significantly higher total fungal abundance than the Malassezia or Saccharomyces species. Of the 25 clinical variables evaluated for potential influences on the oral mycobiome, significant effects were associated with caries status, geographical site of sampling, sex, HIV under highly active antiretroviral therapy (HAART), and missing teeth, in rank order of statistical significance. Investigating specific interactions between fungi and bacteria in the samples often showed Candida species positively correlated with Firmicutes or Actinobacteria and negatively correlated with Fusobacteria, Proteobacteria, and Bacteroidetes Our data suggest that the oral mycobiome, while diverse, is often dominated by a limited number of species per individual; is affected by several clinical variables, including HIV positivity and HAART; and shows genera-specific associations with bacterial groups.IMPORTANCE The oral microbiome is likely a key element of homeostasis in the oral cavity. With >600 bacterial species and >160 fungal species comprising the oral microbiome, influences on its composition can have an impact on both local and systemic health. We recently reported significant effects of HIV and several other clinical variables on the oral bacterial community in a large cohort of HIV-positive and -negative subjects. We describe here a comprehensive analysis of the oral mycobiome in the same cohort. Similar to the bacterial community, HIV under highly active antiretroviral therapy (HAART) had a significant impact on the mycobiome composition, but with less impact compared to other clinical variables. Additionally, unlike the oral bacterial microbiome, the oral mycobiome is often dominated by a single species with 4 major clusters of fungal communities. Together, these results suggest the oral mycobiome has distinct properties compared with the oral bacterial community, although both are equally impacted by HIV.

Acquisition of oral microbiota is driven by environment, not host genetics.

BACKGROUND: The oral microbiota is acquired very early, but the factors shaping its acquisition are not well understood. Previous studies comparing monozygotic (MZ) and dizygotic (DZ) twins have suggested that host genetics plays a role. However, all twins share an equal portion of their parent's genome, so this model is not informative for studying parent-to-child transmission. We used a novel study design that allowed us to directly examine the genetics of transmission by comparing the oral microbiota of biological versus adoptive mother-child dyads. RESULTS: No difference was observed in how closely oral bacterial community profiles matched for adoptive versus biological mother-child pairs, indicating little if any effect of host genetics on the fidelity of transmission. Both adopted and biologic children more closely resembled their own mother as compared to unrelated women, supporting the role of contact and environment. Mother-child strain similarity increased with the age of the child, ruling out early effects of host genetic influence that are lost over time. No effect on the fidelity of mother-child strain sharing from vaginal birth or breast feeding was seen. Analysis of extended families showed that fathers and mothers were equally similar to their children, and that cohabitating couples showed even greater strain similarity than mother-child pairs. These findings support the role of contact and shared environment, and age, but not genetics, as determinants of microbial transmission, and were consistent at both species and strain level resolutions, and across multiple oral habitats. In addition, analysis of individual species all showed similar results. CONCLUSIONS: The host is clearly active in shaping the composition of the oral microbiome, since only a few of the many bacterial species in the larger environment are capable of colonizing the human oral cavity. Our findings suggest that these host mechanisms are universally shared among humans, since no effect of genetic relatedness on fidelity of microbial transmission could be detected. Instead our findings point towards contact and shared environment being the driving factors of microbial transmission, with a unique combination of these factors ultimately shaping the highly personalized human oral microbiome. Video abstract.

Significant effect of HIV/HAART on oral microbiota using multivariate analysis.

Persons infected with HIV are particularly vulnerable to a variety of oral microbial diseases. Although various study designs and detection approaches have been used to compare the oral microbiota of HIV-negative and HIV-positive persons, both with and without highly active antiretroviral therapy (HAART), methods have varied, and results have not been consistent or conclusive. The purpose of the present study was to compare the oral bacterial community composition in HIV-positive persons under HAART to an HIV-negative group using 16S rRNA gene sequence analysis. Extensive clinical data was collected, and efforts were made to balance the groups on clinical variables to minimize confounding. Multivariate analysis was used to assess the independent contribution of HIV status. Eighty-nine HIV-negative participants and 252 HIV-positive participants under HAART were sampled. The independent effect of HIV under HAART on the oral microbiome was statistically significant, but smaller than the effect of gingivitis, periodontal disease, smoking, caries, and other clinical variables. In conclusion, a multivariate comparison of a large sample of persons with HIV under HAART to an HIV-negative control group showed a complex set of clinical features that influenced oral bacterial community composition, including the presence of HIV under HAART.

Oral microbial dysbiosis linked to worsened periodontal condition in rheumatoid arthritis patients.

Rheumatoid arthritis (RA) is an autoimmune disease characterized by joint inflammation. Individuals with RA have a higher risk of periodontitis and periodontitis has been linked to RA through the production of enzymes by periodontal pathogens that citrullinate proteins. This linkage is supported by findings that periodontitis is associated with increased RA severity and treatment of periodontitis can improve the symptoms of RA. The possible mechanism for this association is through dysbiosis of the oral microbiota triggered by RA-induced systemic inflammation. We examined the RA status of subjects by measuring the number of tender and swollen joints, anti-citrullinated protein antibody and rheumatoid factor. Periodontal disease status and salivary cytokine levels were measured, and dental plaque analyzed by 16S rRNA high throughput sequencing. RA patients had a higher bacterial load, a more diverse microbiota, an increase in bacterial species associated with periodontal disease, more clinical attachment loss, and increased production of inflammatory mediators including IL-17, IL-2, TNF, and IFN-γ. Furthermore, changes in the oral microbiota were linked to worse RA conditions. Our study provides new insights into the bi-directional relationship between periodontitis and RA and suggest that monitoring the periodontal health of RA patients is particularly important.

Correction to: High-resolution ISR amplicon sequencing reveals personalized oral microbiome.

Following publication of the original article, the authors recognized that the left and right panels in Fig. 6b had been inadvertently switched during reformatting.

High-resolution ISR amplicon sequencing reveals personalized oral microbiome.

BACKGROUND: Sequencing of the 16S rRNA gene has been the standard for studying the composition of microbial communities. While it allows identification of bacteria at the level of species, this method does not usually provide sufficient information to resolve communities at the sub-species level. Species-level resolution is not adequate for studies of transmission or stability or for exploring subspecies variation in disease association. Strain level analysis using whole metagenome shotgun sequencing has significant limitations that can make it unsuitable for large-scale studies. Achieving sufficient depth of sequencing can be cost-prohibitive, and even with adequate coverage, deconvoluting complex communities such as the oral microbiota is computationally very challenging. Thus, there is a need for high-resolution, yet cost-effective, high-throughput methods for characterizing microbial communities. RESULTS: Significant improvement in resolution for amplicon-based bacterial community analysis was achieved by combining amplicon sequencing of a high-diversity marker gene, the ribosomal 16-23S intergenic spacer region (ISR), with a probabilistic error modeling based denoising algorithm, DADA2. The resolving power of this new approach was compared to that of both standard and high-resolution 16S-based approaches using a set of longitudinal subgingival plaque samples. The ISR strategy resulted in a 5.2-fold increase in community resolution compared to reference-based 16S rRNA gene analysis and showed 100% accuracy in predicting the correct source of a clinical sample. Individuals' microbial communities were highly personalized, and although they exhibited some drift in membership and levels over time, that difference was always smaller than the differences between any two subjects, even after 1 year. The construction of an ISR database from publicly available genomic sequences allowed us to explore genomic variation within species, resulting in the identification of multiple variants of the ISR for most species. CONCLUSIONS: The ISR approach resulted in significantly improved resolution of communities and revealed a highly personalized human oral microbiota that was stable over 1 year. Multiple ISR types were observed for all species examined, demonstrating a high level of subspecies variation in the oral microbiota. The approach is high-throughput, high-resolution yet cost-effective, allowing subspecies-level community fingerprinting at a cost comparable to that of 16S rRNA gene amplicon sequencing. It will be useful for a range of applications that require high-resolution identification of organisms, including microbial tracking, community fingerprinting, and potentially for identification of virulence-associated strains.

Enzymatic production and emission of floral scent volatiles in Jasminum sambac.

Floral scent composed of low molecular weight volatile organic compounds. The sweet fragrance of any evening blooming flower is dominated by benzenoid and terpenoid volatile compounds. Floral scent of Jasminum sambac (Oleaceae) includes three major benzenoid esters - benzylacetate, methylbenzoate, and methylsalicylate and three major terpene compounds viz. (E)-ß-ocimene, linalool and α-farnesene. We analyzed concentrations and emission rates of benzenoids and terpenoids during the developmental stages of J. sambac flower. In addition to spatial emission from different floral parts, we studied the time-course mRNA accumulations of phenylalanine ammonia-lyase (PAL) and the two representative genes of terpenoid pathway, namely 1-deoxy-d-xylulose 5-phosphate reductoisomerase (DXR) and terpene synthase (TPS). Further, in vitro activities of several enzymes of phenylpropanoid/benzenoid pathway viz., PAL and acetyl-coenzyme A: benzylalcohol acetyltransferase (BEAT), S-adenosyl-l-methionine: benzoic acid carboxyl methyl transferase (BAMT) and S-adenosyl-l-methionine: salicylic acid carboxyl methyltransferase (SAMT) were studied. All the above enzyme activities along with the in vitro activities of DXR and TPS were found to follow a certain rhythm as observed in the emission of different benzenoid and terpenoid compounds. Linalool emission peaked after petal opening and coincided with maximal expression of JsTPS gene as evidenced from RT-PCR analyses (semi-quantitative). The maximum transcript accumulation of this gene was observed in flower petals, indicating that the petals of J. sambac flower play an important role as a major contributor of volatile precursors. The transcripts accumulation of JsDXR and JsTPS in different developmental stages and in different floral part showed that emissions of terpenoid volatiles in J. sambac flower are partially regulated at transcription levels.

Synthesis of argentojarosite with simulated bioleaching solutions produced by Acidithiobacillus ferrooxidans.

Argentojarosite (AgFe3(SO4)2(OH)6) is formed as a secondary phase in Ag-catalyzed bioleaching of chalcopyrite (CuFeS2), but to date very little is known about the paragenesis or characteristics of this silver-containing compound. The purpose of this study was to synthesize argentojarosite via biological oxidation of 120mM ferrous sulfate by Acidithiobacillus ferrooxidans. Because of its toxicity to A. ferrooxidans, Ag(+) (as AgNO3) was added to spent culture media (pH2) after complete oxidation of ferrous sulfate. Schwertmannite (ideally Fe8O8(OH)6(SO4)) was precipitated during the iron oxidation phase, and subsequent Ag(+) addition resulted in the formation of argentojarosite. Contact time (8h, 5d, and 14d) and Ag(+) concentration (0, 5, 20, and 40mM) were used as variables in these experiments. Synthesis of argentojarosite, schwertmannite and other mineral phases was confirmed through X-ray diffraction analysis. Additional analyses of solid-phase oxidation products included elemental composition, color and specific surface area. The sample synthesized in the presence of 40mM Ag(+) and with 14d contact time yielded an X-ray diffraction pattern of well crystallized argentojarosite, and its elemental composition closely matched the calculated Ag, Fe, and S contents of ideal argentojarosite. The color and surface area of the remaining samples were influenced by the presence of residual schwertmannite. This phase remained stable over the time course of 14d when no Ag(+) was present in the system. When equilibrations were extended to 42d, partial conversion of reference schwertmannite to goethite was noted in the absence of Ag. In the presence of 20mM or 40mM Ag over the same time course, some formation of argentojarosite was also noted. In this case, schwertmannite was the only source of Fe and SO4 for argentojarosite formation.

GPU-powered Shotgun Stochastic Search for Dirichlet process mixtures of Gaussian Graphical Models.

Gaussian graphical models are popular for modeling high-dimensional multivariate data with sparse conditional dependencies. A mixture of Gaussian graphical models extends this model to the more realistic scenario where observations come from a heterogenous population composed of a small number of homogeneous sub-groups. In this paper we present a novel stochastic search algorithm for finding the posterior mode of high-dimensional Dirichlet process mixtures of decomposable Gaussian graphical models. Further, we investigate how to harness the massive thread-parallelization capabilities of graphical processing units to accelerate computation. The computational advantages of our algorithms are demonstrated with various simulated data examples in which we compare our stochastic search with a Markov chain Monte Carlo algorithm in moderate dimensional data examples. These experiments show that our stochastic search largely outperforms the Markov chain Monte Carlo algorithm in terms of computing-times and in terms of the quality of the posterior mode discovered. Finally, we analyze a gene expression dataset in which Markov chain Monte Carlo algorithms are too slow to be practically useful.

Redirection of metabolite biosynthesis from hydroxybenzoates to volatile terpenoids in green hairy roots of Daucus carota.

MAIN CONCLUSION: A metabolic shift in green hairy root cultures of carrot from phenylpropanoid/benzenoid biosynthesis toward volatile isoprenoids was observed when compared with the metabolite profile of normal hairy root cultures. Hairy roots cultures of Daucus carota turned green under continuous illumination, while the content of the major phenolic compound p-hydroxybenzoic acid (p-HBA) was reduced to half as compared to normal hairy roots cultured in darkness. p-Hydroxybenzaldehyde dehydrogenase (HBD) activity was suppressed in the green hairy roots. However, comparative volatile analysis of 14-day-old green hairy roots revealed higher monoterpene and sesquiterpene contents than found in normal hairy roots. Methyl salicylate content was higher in normal hairy roots than in green ones. Application of clomazone, an inhibitor of 1-deoxy-D-xylulose 5-phosphate synthase (DXS), reduced the amount of total monoterpenes and sesquiterpenes in green hairy roots compared to normal hairy roots. However, methyl salicylate content was enhanced in both green and normal hairy roots treated with clomazone as compared to their respective controls. Because methyl-erythritol 4-phosphate (MEP) and phenylpropanoid pathways, respectively, contribute to the formation of monoterpenes and phenolic acids biosynthesis, the activities of enzymes regulating those pathways were measured in terms of their in vitro activities, in both green and normal hairy root cultures. These key enzymes were 1-deoxy-D-xylulose 5-phosphate reductoisomerase (DXR), an early regulatory enzyme of the MEP pathway, pyruvate kinase (PK), an enzyme of primary metabolism related to the MEP pathway, shikimate dehydrogenase (SKDH) which is involved in biosynthesis of aromatic amino acids, and phenylalanine ammonia-lyase (PAL) that catalyzes the first step of phenylpropanoid biosynthesis. Activities of DXR and PK were higher in green hairy roots as compared to normal ones, whereas the opposite trend was observed for SKDH and PAL activities. Gene expression analysis of DXR and PAL showed trends similar to those for the respective enzyme activities. Based on these observations, we suggest a possible redirection of metabolites from the primary metabolism toward isoprenoid biosynthesis, limiting the phenolic biosynthetic pathway in green hairy roots grown under continuous light.

Metabolic shift from withasteroid formation to phenylpropanoid accumulation in cryptogein-cotransformed hairy roots of Withania somnifera (L.) Dunal.

Cotransformed hairy roots containing a gene that encodes a fungal elicitor protein, ß-cryptogein, were established in Withania somnifera, a medicinal plant widely used in Indian systems of medicine. To find out whether ß-cryptogein protein endogenously elicits the pathway of withasteroid biosynthesis, withaferin A and withanolide A contents along with transcript accumulation of farnesyl pyrophosphate (FPP) synthase, 3-hydroxy-3-methyl-glutaryl-CoA reductase (HMGR), and sterol glycosyltransferase (SGT) were analyzed in both cryptogein-cotransformed and normal hairy roots of W. somnifera. It was observed that the withaferin A and withanolide A contents were drastically higher in normal hairy roots than cryptogein-cotransformed ones. Similar trends were also observed on the levels of transcript accumulation. Subsequently, the enzyme activity of phenylalanine ammonia lyase (PAL), one of the key enzymes of phenylpropanoid pathway, was measured in both cryptogein-cotransformed and normal hairy roots of W. somnifera along with the levels of PAL transcript accumulation. Upliftment of PAL activity was observed in cryptogein-cotransformed hairy roots as compared to the normal ones, and the PAL expression also reflected a similar trend, i.e., enhanced expression in the cryptogein-cotransformed lines. Upliftment of wall-bound ferulic acid accumulation was also observed in the cryptogein-cotransformed lines, as compared to normal hairy root lines. Thus, the outcome of the above studies suggests a metabolic shift from withanolide accumulation to phenylpropanoid biosynthesis in cryptogein-cotransformed hairy roots of W. somnifera.

Combating photooxidative stress in green hairy roots of Daucus carota cultivated under light irradiation.

The light-dependent generation of active oxygen species, which can disrupt normal metabolic process of plant, is termed as photo-oxidative stress. Plants are equipped with enzymatic and non-enzymatic antioxidative defence system to reduce the effect of such stress. Hairy root culture of Daucus carota when cultivated under continuous illumination (250 µmol m(-2)s(-1)) turned green. To know the reason behind that and photo-oxidative stress response in green hairy roots, activities of several antioxidant enzymes were measured. When compared with normal hairy roots, green hairy roots showed an enhanced superoxide dismutase (SOD) activity. Treatment with a SOD inhibitor diethyldithiocarbamate led to suppression of SOD activity in a concentration-dependent manner in green hairy roots. Interestingly, SOD-suppressed root showed three-fold enhanced caffeic acid glucoside accumulation in the soluble fraction as compared to untreated ones. While ascorbate peroxidase activity showed marginal increase in green hairy roots, a decrease in the activities of guaiacol peroxidase and catalase were observed. SDS-PAGE of crude protein profile from green hairy roots showed a distinct band, which was absent in normal hairy roots. MALDI-TOF-MS/MS analysis of the extracted protein confirmed it as the large subunit of RuBisCO. RT-PCR based expression analysis of betaine aldehyde dehydrogenase showed enhanced transcript levels in green hairy roots as compared to normal hairy roots, whereas reverse trends were observed with the transcripts accumulation for phenylalanine ammonia-lyase and chalcone synthase. These findings corroborate with the in vitro BADH activities in hairy roots, and thus indicate an important role of this stress enzyme in combating photo-oxidative stress in green hairy roots upon continuous light exposure.

Alternative oxidase (AOX) and phenolic metabolism in methyl jasmonate-treated hairy root cultures of Daucus carota L.

Methyl-jasmonate (MJ)-treated hairy roots of Daucus carota L. were used to study the influence of alternative oxidase (AOX) in phenylpropanoid metabolism. Phenolic acid accumulation, as well as total flavonoids and lignin content of the MJ-treated hairy roots were decreased by treatment with salicylhydroxamic acid (SHAM), a known inhibitor of AOX. The inhibitory effect of SHAM was concentration dependent. Treatment with propyl gallate (PG), another inhibitor of AOX, also had a similar inhibitory effect on accumulation of phenolic acid, total flavonoids and lignin. The transcript levels of two DcAOX genes (DcAOX2a and DcAOX1a) were monitored at selected post-elicitation time points. A notable rise in the transcript levels of both DcAOX genes was observed preceding the MJ-induced enhanced accumulation of phenolics, flavonoids and lignin. An appreciable increase in phenylalanine ammonia-lyase (PAL) transcript level was also observed prior to enhanced phenolics accumulation. Both DcAOX genes showed differential transcript accumulation patterns after the onset of elicitation. The transcript levels of DcAOX1a and DcAOX2a attained peak at 6hours post elicitation (hpe) and 12hpe, respectively. An increase in the transcript levels of both DcAOX genes preceding the accumulation of phenylpropanoid-derivatives and lignin showed a positive correlation between AOX activity and phenylpropanoid biosynthesis. The results provide important new insight about the influence of AOX in phenylpropanoid biosynthesis.