NIR and Py-mbms coupled with multivariate data analysis as a high-throughput biomass characterization technique: a review

Quantitative analysis of biopolymers in lignocellulosic biomass feedstocks via laser-assisted micro-pyrolysis flowing atmospheric-pressure afterglow high-resolution ambient mass spectrometry

Herein, a diode laser-assisted micro-pyrolysis (LAMP) technique coupled with FAPA high resolution mass spectrometry (HRMS) is demonstrated for fast chemical characterization of lignocellulosic biomass feedstocks. The solid lignocellulosic biomass can be analyzed directly with minimal sample preparation. The mass spectra of the pyrolysis products are interpreted with the aid of data visualization tools such as Kendrick mass defect (KMD) plots and van Krevelen plots. Furthermore, quantitation of lignin/cellulose/hemicellulose, sugar contents of glucan/xylan/galactan/arabinan and lignin monomeric unit S/G is achieved with good accuracy and precision, through multivariate analysis methods, including partial least squares regression (PLSR) and support vector regression (SVR).

Screening and validating of endogenous reference genes in Chlorella sp. TLD 6B under abiotic stress

Chlorella sp. TLD 6B, a microalgae growing in the Taklamakan Desert, Xinjiang of China, is a good model material for studying the physiological and environmental adaptation mechanisms of plants in their arid habitats, as its adaptation to the harsh desert environment has led to its strong resistance. However, when using real-time quantitative polymerase chain reaction (RT-qPCR) to analyze the gene expression of this algae under abiotic stress, it is essential to find the suitable endogenous reference genes so to obtain reliable results. This study assessed the expression stability of 9 endogenous reference genes of Chlorella sp. TLD 6B under four abiotic stresses (drought, salt, cold and heat). These genes were selected based on the analysis results calculated by the three algorithmic procedures of geNorm, NormFinder, and BestKeeper, which were ranked by refinder. Our research showed that 18S and GTP under drought stress, 18S and IDH under salt stress, CYP and 18S under cold stress, GTP and IDH under heat stress were the most stable endogenous reference genes. Moreover, UBC and 18S were the most suitable endogenous reference gene combinations for all samples. In contrast, GAPDH and α-TUB were the two least stable endogenous reference genes in all experimental samples. Additionally, the selected genes have been verified to be durable and reliable by detecting POD and PXG3 genes using above endogenous reference genes. The identification of reliable endogenous reference genes guarantees more accurate RT-qPCR quantification for Chlorella sp. TLD 6B, facilitating functional genomics studies of deserts Chlorella as well as the mining of resistance genes.

Variations in the morphological and chemical composition of the rhizomes of Polygonatum species based on a common garden experiment

Polygonatum species have great potential in fighting chronic and hidden hunger. In this study, five Polygonatum species collected from different populations were cultivated in a common garden for 4 years. The species mainly differed in yield, saponin and polysaccharide contents, stem diameter, leaf width, inflorescence length, and floret inflorescence length. P. cyrtonema (PC) provides high-quality yield when planted in Zhejiang, with output as high as 7.5 tons per hectare and a promising breeding potential. Moreover, stem diameter can be used as an indicator of the harvest in the screening of varieties. In addition, the formation of plant genetic traits from different provenances is affected by the climatic factors of the origin. Furthermore, near-infrared spectroscopy combined with chemometrics for polysaccharide and saponin quantitation provides a rapid assessment of PC quality. Our findings provide a scientific basis for the development and sustainable utilization of PC as a high-yielding and high-quality forest crop.

Selection and validation of appropriate reference genes for RT-qPCR analysis of Nitraria sibirica under various abiotic stresses

BACKGROUND

Nitraria sibirica Pall. is a halophytic shrub with strong environmental adaptability that can survive in extremely saline-alkali and drought-impacted environments. Gene expression analysis aids in the exploration of the molecular mechanisms of plant responses to abiotic stresses. RT-qPCR is the most common technique for studying gene expression. Stable reference genes are a prerequisite for obtaining accurate target gene expression results in RT-qPCR analysis.

RESULTS

In this study, a total of 10 candidate reference genes were selected from the transcriptome of N. sibirica, and their expression stability in leaves and roots under different treatment conditions (salt, alkali, drought, cold, heat and ABA) was evaluated with the geNorm, NormFinder, BestKeeper, comparative ΔCt and RefFinder programs. The results showed that the expression stability of the candidate reference genes was dependent on the tissue and experimental conditions tested. ACT7 combined with R3H, GAPDH, TUB or His were the most stable reference genes in the salt- or alkali-treated leaves, salt-treated roots and drought-treated roots, respectively; R3H and GAPDH were the most suitable combination for drought-treated leaves, heat-treated root samples and ABA-treated leaves; DIM1 and His maintained stable expression in roots under alkali stress; and TUB combined with R3H was stable in ABA-treated roots. TBCB and GAPDH exhibited stable expression in heat-treated leaves; TBCB, R3H, and ERF3A were stable in cold-treated leaves; and the three most stable reference genes for cold-treated roots were TBCB, ACT11 and DIM1. The reliability of the selected reference genes was further confirmed by evaluating the expression patterns of the NsP5CS gene under the six treatment conditions.

CONCLUSION

This study provides a theoretical reference for N. sibirica gene expression standardization and quantification under various abiotic stress conditions and will help to reveal the molecular mechanisms that confer stress tolerance to N. sibirica.

Exploration of the Interrelationship within Biomass Pyrolysis Liquid Composition Based on Multivariate Analysis

The diverse utilization of pyrolysis liquid is closely related to its chemical compositions. Several factors affect PA compositions during the preparation. In this study, multivariate statistical analysis was conducted to assess PA compositions data obtained from published paper and experimental data. Results showed the chemical constituents were not significantly different in different feedstock materials. Acids and phenolics contents were 31.96% (CI: 25.30−38.62) and 26.50% (CI: 21.43−31.57), respectively, accounting for 58.46% (CI: 46.72−70.19) of the total relative contents. When pyrolysis temperatures range increased to above 350 °C, acids and ketones contents decreased by more than 5.2-fold and 1.53-fold, respectively, whereas phenolics content increased by more than 2.1-fold, and acetic acid content was the highest, reaching 34.16% (CI: 25.55−42.78). Correlation analysis demonstrated a significantly negative correlation between acids and phenolics (r2 = −0.43, p < 0.001) and significantly positive correlation between ketones and alcohols (r2 = 0.26, p < 0.05). The pyrolysis temperatures had a negative linear relationship with acids (slope = −0.07, r2 = 0.16, p < 0.001) and aldehydes (slope = −0.02, r2 = 0.09, p < 0.05) and positive linear relationship with phenolics (slope = 0.04, r2 = 0.07, p < 0.05). This study provides a theoretical reference of PA application.

Evaluation of Angelica decursiva reference genes under various stimuli for RT-qPCR data normalization

Angelica decursiva is one of the lending traditional Chinese medicinal plants producing coumarins. Notably, several studies have focused on the biosynthesis and not the RT-qPCR (quantitative real-time reverse transcription polymerase chain reaction) study of coumarins. This RT-qPCR technique has been extensively used to investigate gene expression levels in plants and the selection of reference genes which plays a crucial role in standardizing the data form the RT-qPCR analysis. In our study, 11 candidate reference genes were selected from the existing transcriptome data of Angelica decursiva. Here, four different types of statistical algorithms (geNorm, NormFinder, BestKeeper, and Delta Ct) were used to calculate and evaluate the stability of gene expression under different external treatments. Subsequently, RefFinder analysis was used to determine the geometric average of each candidate gene ranking, and to perform comprehensive index ranking. The obtained results showed that among all the 11 candidate reference genes, SAND family protein (SAND), protein phosphatase 2A gene (PP2A), and polypyrimidine tract-binding protein (PTBP) were the most stable reference genes, where Nuclear cap binding protein 2 (NCBP2), TIP41-like protein (TIP41), and Beta-6-tubulin (TUBA) were the least stable genes. To the best of our knowledge, this work is the first to evaluate the stability of reference genes in the Angelica decursiva which has provided an important foundation on the use of RT-qPCR for an accurate and far-reaching gene expression analysis in this medicinal plant.

Identification and selection of reference genes for gene expression analysis by quantitative real-time PCR in Suaeda glauca's response to salinity

Quantitative real-time polymerase chain reaction (qPCR) using a stable reference gene is widely used for gene expression research. Suaeda glauca L. is a succulent halophyte and medicinal plant that is extensively used for phytoremediation and extraction of medicinal compounds. It thrives under high-salt conditions, which promote the accumulation of high-value secondary metabolites. However, a suitable reference gene has not been identified for gene expression standardization in S. glauca under saline conditions. Here, 10 candidate reference genes, ACT7, ACT11, CCD1, TUA5, UPL1, PP2A, DREB1D, V-H⁺-ATPase, MPK6, and PHT4;5, were selected from S. glauca transcriptome data. Five statistical algorithms (ΔCq, geNorm, NormFinder, BestKeeper, and RefFinder) were applied to determine the expression stabilities of these genes in 72 samples at different salt concentrations in different tissues. PP2A and TUA5 were the most stable reference genes in different tissues and salt treatments, whereas DREB1D was the least stable. The two reference genes were sufficient to normalize gene expression across all sample sets. The suitability of identified reference genes was validated with MYB and AP2 in germinating seeds of S. glauca exposed to different NaCl concentrations. Our study provides a foundational framework for standardizing qPCR analyses, enabling accurate gene expression profiling in S. glauca.

Rapid determination of total phenolic content of whole wheat flour using near-infrared spectroscopy and chemometrics

Phenolics in whole wheat products provide many health benefits. Wheat breeders, producers, and end-users are becoming increasingly interested in wheats with higher total phenolic content (TPC). Whole wheat flour with higher phenolics may have greater marketing value in the future. However, conventional methods determining TPC are costly and labor-intensive, which are not practical for wheat breeders to analyze several thousands of lines within a limited timeframe. We presented a novel application of near-infrared spectroscopy for TPC prediction in whole wheat flour. The optimal regression model demonstrated R² values of 0.92 and 0.90 for the calibration and validation sets, and a residual prediction deviation value of 3.4. The NIR method avoids the tedious extraction and TPC assay procedures, making it more convenient and cost-effective. Our result also demonstrated that NIR can accurately quantify phenolics even at low concentration (less than 0.2%) in the food matrix such as whole wheat flour.

Non-Destructive Evaluation Techniques and What They Tell Us about Wood Property Variation

To maximize utilization of our forest resources, detailed knowledge of wood property variation and the impacts this has on end-product performance is required at multiple scales (within and among trees, regionally). As many wood properties are difficult and time-consuming to measure our knowledge regarding their variation is often inadequate as is our understanding of their responses to genetic and silvicultural manipulation. The emergence of many non-destructive evaluation (NDE) methodologies offers the potential to greatly enhance our understanding of the forest resource; however, it is critical to recognize that any technique has its limitations and it is important to select the appropriate technique for a given application. In this review, we will discuss the following technologies for assessing wood properties both in the field: acoustics, Pilodyn, Resistograph and Rigidimeter and the lab: computer tomography (CT) scanning, DiscBot, near infrared (NIR) spectroscopy, radial sample acoustics and SilviScan. We will discuss these techniques, explore their utilization, and list applications that best suit each methodology. As an end goal, NDE technologies will help researchers worldwide characterize wood properties, develop accurate models for prediction, and utilize field equipment that can validate the predictions. The continued advancement of NDE technologies will also allow researchers to better understand the impact on wood properties on product performance.

Effect of crystallinity on pretreatment and enzymatic hydrolysis of lignocellulosic biomass based on multivariate analysis

In this work, multivariate data analysis was employed to correlate variables of pretreatment process of lignocellulosic biomass. Principal component analysis and partial least square methods were performed to get the inner-relationship and data interpretation between the crystallinity and other parameters of mechanical refining-assisted sodium hydroxide pretreatment followed by enzymatic saccharification of corn stover. The PCA and PLS models showed that Sodium hydroxide dosage, mechanical refining treatment, lignin removal rate and crystallinity had close inner-related relationship with the efficiency of pretreatment and enzymolysis. Alkaline reaction and mechanical refining treatment had strong influence on the crystallinity. Multivariate data analysis revealed that pretreated corn stover samples with lower crystallinity were more easily hydrolyzed by enzyme and could get more final reducing sugar. This work could offer a new methodology to get further understanding of effect of crystallinity on the crop residue lignocellulosic biomass conversion process.

Identification and validation of reference genes for real-time quantitative RT-PCR analysis in jute

BACKGROUND

With the availability of genome sequences, gene expression analysis of jute has drawn considerable attention for understanding the regulatory mechanisms of fiber development and improving fiber quality. Gene expression profiles of a target gene can provide valuable clues towards the understanding of its biological function. Reverse transcription quantitative real-time PCR (qRT-PCR) is the best method for targeted gene expression analysis due to its sensitivity and reproducibility. However, calculating relative expression requires reference genes, which must be stable across various biological conditions. For this purposes, 11 prospective genes namely, 28S RNA, ACT7, CYP, EF1A, EF2, ETIF3E, GAPDH, PP2Ac, PTB, UBC2 and UBI1 were evaluated for their potential use as reference genes in jute.

RESULTS

The expression stabilities of eleven prospective genes were analyzed in various jute plant tissues, such as the root, stick, bark, leaf, flower, seed and fiber, as well as under abiotic (waterlogged, drought and salinity) and biotic stress (infestation with Macrophomina phaseolina) conditions with different time points. All 11 genes were variably expressed in different tissues and stress conditions. To find suitable reference genes in different sample sets, a comprehensive approach based on four statistical algorithms such as GeNorm, BestKeeper, NormFinder the ΔCt was used. The PP2Ac and EF2 genes were the most stably expressed across the different tissues. ACT7 and UBC2 were suitable reference genes under drought stress, and CYP and PP2Ac were the most appropriate after inoculation with Macrophomina phaseolina. Under salinity stress, PP2Ac and UBC2 were the best genes, and ACT7 and PP2Ac were the most suitable under waterlogged conditions.

CONCLUSION

Expression stability of reference genes from jute varied in different tissues and selected experimental conditions. Our results provide a valuable resource for the accurate normalization of gene expression experiments in fiber research for important bast fiber crops.

An NIRS-based assay of chemical composition and biomass digestibility for rapid selection of Jerusalem artichoke clones

BACKGROUND

High-throughput evaluation of lignocellulosic biomass feedstock quality is the key to the successful commercialization of bioethanol production. Currently, wet chemical methods for the determination of chemical composition and biomass digestibility are expensive and time-consuming, thus hindering comprehensive feedstock quality assessments based on these biomass specifications. To find the ideal bioethanol feedstock, we perform a near-infrared spectroscopic (NIRS) assay to rapidly and comprehensively analyze the chemical composition and biomass digestibility of 59 Jerusalem artichoke (Helianthus tuberosus L., abbreviated JA) clones collected from 24 provinces in six regions of China.

RESULTS

The distinct geographical distribution of JA accessions generated varied chemical composition as well as related biomass digestibility (after soluble sugars extraction and mild alkali pretreatment). Notably, the soluble sugars, cellulose, hemicellulose, lignin, ash, and released hexoses, pentoses, and total carbohydrates were rapidly and perfectly predicted by partial least squares regression coupled with model population analyses (MPA), which exhibited significantly higher predictive performance than controls. Subsequently, grey relational grade analysis was employed to correlate chemical composition and biomass digestibility with feedstock quality score (FQS), resulting in the assignment of tested JA clones to five feedstock quality grades (FQGs). Ultimately, the FQGs of JA clones were successfully classified using partial least squares-discriminant analysis model coupled with MPA, attaining a significantly higher correct rate of 97.8% in the calibration subset and 91.1% in the validation subset.

CONCLUSIONS

Based on the diversity of JA clones, the present study has not only rapidly and precisely examined the biomass composition and digestibility with MPA-optimized NIRS models but has also selected the ideal JA clones according to FQS. This method provides a new insight into the selection of ideal bioethanol feedstock for high-efficiency bioethanol production.

Selection and Validation of Novel RT-qPCR Reference Genes under Hormonal Stimuli and in Different Tissues of Santalum album

Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) is a widely used technique to investigate gene expression levels due to its high throughput, specificity, and sensitivity. An appropriate reference gene is essential for RT-qPCR analysis to obtain accurate and reliable results. To date, no reliable reference gene has been validated for the economically tropical tree, sandalwood (Santalum album L.). In this study, 13 candidate reference genes, including 12 novel putative reference genes selected from a large set of S. album transcriptome data, as well as the currently used β-actin gene (ACT), were validated in different tissues (stem, leaf, root and callus), as well as callus tissue under salicylic acid (SA), jasmonic acid methyl ester (MeJA), and gibberellin (GA) treatments using geNorm, NormFinder, BestKeeper, Delta Ct and comprehensive RefFinder algorithms. Several novel candidate reference genes were much more stable than the currently used traditional gene ACT. ODD paired with Fbp1 for SA treatment, CSA and Fbp3 for MeJA treatment, PP2C and Fbp2 for GA treatment, as well as Fbp1 combined with Fbp2 for the total of three hormone treatments were the most accurate reference genes, respectively. FAB1A, when combined with PP2C, was identified as the most suitable reference gene combination for the four tissues tested, while the combination of HLMt, PPR and FAB1A were the most optimal reference genes for all of the experimental samples. In addition, to verify our results, the relative expression level of the SaSSy gene was evaluated by the validated reference genes and their combinations in the three S. album tissues and under MeJA treatment. The evaluated reference genes in this study will improve the accuracy of RT-qPCR analysis and will benefit S. album functional genomics studies in different tissues and under hormone stimuli in the future.

Identification of suitable internal control genes for transcriptional studies in Eleusine coracana under different abiotic stress conditions

Finger millet [Eleusine coracana (L.) Gaertn] is an excellent food and forage crop of arid and semiarid areas in Africa and Asia. It is well adapted to drought, heat, high salinity, poor soil fertility and low pH with an efficient C₄ carbon fixation mechanism for high yield potential. To normalize the target gene expression data, the identification of suitable reference genes is essential. Ten candidate reference genes were selected and their expression stability was analyzed in various samples treated with different abiotic stress conditions. Five different statistical algorithms: geNorm, NormFinder, BestKeeper, ΔCt, and RefFinder were used to determine the stability of these genes. Our results revealed GAPDH, EEF1a, ACT and CYC as highly stable reference genes and PP2A and eIF4A as least stable reference genes across all the samples and suggesting that these genes could be used for accurate transcript normalization under abiotic stress. To the best of our knowledge, this is the first report on identification of suitable reference genes for accurate transcript normalization using qRT-PCR in finger millet under abiotic stress.

Housekeeping in Tephritid insects: the best gene choice for expression analyses in the medfly and the olive fly

Real-time quantitative-PCR has been a priceless tool for gene expression analyses. The reaction, however, needs proper normalization with the use of housekeeping genes (HKGs), whose expression remains stable throughout the experimental conditions. Often, the combination of several genes is required for accurate normalization. Most importantly, there are no universal HKGs which can be used since their expression varies among different organisms, tissues or experimental conditions. In the present study, nine common HKGs (RPL19, tbp, ubx, GAPDH, α-TUB, β-TUB, 14-3-3zeta, RPE and actin3) are evaluated in thirteen different body parts, developmental stages and reproductive and olfactory tissues of two insects of agricultural importance, the medfly and the olive fly. Three software programs based on different algorithms were used (geNorm, NormFinder and BestKeeper) and gave different ranking of HKG stabilities. This confirms once again that the stability of common HKGs should not be taken for granted and demonstrates the caution that is needed in the choice of the appropriate HKGs. Finally, by estimating the average of a standard score of the stability values resulted by the three programs we were able to provide a useful consensus key for the choice of the best HKG combination in various tissues of the two insects.

Sustainable sources need reliable standards

This review discusses the challenges within the research area of modern biomass fractionation and valorization. The current pulping industry focuses on pulp production and the resulting cellulose fiber. Hemicellulose and lignin are handled as low value streams for process heat and the regeneration of process chemicals. The paper and pulp industry have therefore developed analytical techniques to evaluate the cellulose fiber, while the other fractions are given a low priority. In a strive to also use the hemicellulose and lignin fractions of lignocellulosic biomass, moving towards a biorefining concept, there are severe shortcomings with the current pulping techniques and also in the analysis of the biomass. Lately, new fractionation techniques have emerged which valorize a larger extent of the lignocellulosic biomass. This progress has disclosed the shortcomings in the analysis of mainly the hemicellulose and lignin structure and properties. To move the research field forward, analytical tools for both the raw material, targeting all the wood components, and the generated fractions, as well as standardized methods for evaluating and reporting yields are desired. At the end of this review, a discourse on how such standardizations can be implemented is given.

High-throughput analysis of chemical components and theoretical ethanol yield of dedicated bioenergy sorghum using dual-optimized partial least squares calibration models

BACKGROUND

Due to its chemical composition and abundance, lignocellulosic biomass is an attractive feedstock source for global bioenergy production. However, chemical composition variations interfere with the success of any single methodology for efficient bioenergy extraction from diverse lignocellulosic biomass sources. Although chemical component distributions could guide process design, they are difficult to obtain and vary widely among lignocellulosic biomass types. Therefore, expensive and laborious "one-size-fits-all" processes are still widely used. Here, a non-destructive and rapid analytical technology, near-infrared spectroscopy (NIRS) coupled with multivariate calibration, shows promise for addressing these challenges. Recent advances in molecular spectroscopy analysis have led to methodologies for dual-optimized NIRS using sample subset partitioning and variable selection, which could significantly enhance the robustness and accuracy of partial least squares (PLS) calibration models. Using this methodology, chemical components and theoretical ethanol yield (TEY) values were determined for 70 sweet and 77 biomass sorghum samples from six sweet and six biomass sorghum varieties grown in 2013 and 2014 at two study sites in northern China.

RESULTS

Chemical components and TEY of the 147 bioenergy sorghum samples were initially analyzed and compared using wet chemistry methods. Based on linear discriminant analysis, a correct classification assignment rate (either sweet or biomass type) of 99.3% was obtained using 20 principal components. Next, detailed statistical analysis demonstrated that partial optimization using sample set partitioning based on joint X-Y distances (SPXY) for sample subset partitioning enhanced the robustness and accuracy of PLS calibration models. Finally, comparisons between five dual-optimized strategies indicated that competitive adaptive reweighted sampling coupled with the SPXY (CARS-SPXY) was the most efficient and effective method for improving predictive performance of PLS multivariate calibrations.

CONCLUSIONS

As a dual-optimized methodology, sample subset partitioning combined with variable selection is an efficient and straightforward strategy to enhance the accuracy and robustness of NIRS models. This knowledge should facilitate generation of improved lignocellulosic biomass feedstocks for bioethanol production. Moreover, methods described here should have wider applicability for use with feedstocks incorporating multispecies biomass resource streams.

Selection of reliable reference genes for normalization of quantitative RT-PCR from different developmental stages and tissues in amphioxus

Amphioxus is a closest living proxy to the ancestor of cephalochordates with vertebrates, and key animal for novel understanding in the evolutionary origin of vertebrate body plan, genome, tissues and immune system. Reliable analyses using quantitative real-time PCR (qRT-PCR) for answering these scientific questions is heavily dependent on reliable reference genes (RGs). In this study, we evaluated stability of thirteen candidate RGs in qRT-PCR for different developmental stages and tissues of amphioxus by four independent (geNorm, NormFinder, BestKeeper and deltaCt) and one comparative algorithms (RefFinder). The results showed that the top two stable RGs were the following: (1) S20 and 18 S in thirteen developmental stages, (2) EF1A and ACT in seven normal tissues, (3) S20 and L13 in both intestine and hepatic caecum challenged with lipopolysaccharide (LPS), and (4) S20 and EF1A in gill challenged with LPS. The expression profiles of two target genes (EYA and HHEX) in thirteen developmental stages were used to confirm the reliability of chosen RGs. This study identified optimal RGs that can be used to accurately measure gene expression under these conditions, which will benefit evolutionary and functional genomics studies in amphioxus.

Burkholderia phytofirmans Inoculation-Induced Changes on the Shoot Cell Anatomy and Iron Accumulation Reveal Novel Components of Arabidopsis-Endophyte Interaction that Can Benefit Downstream Biomass Deconstruction

It is known that plant growth promoting bacteria (PGPB) elicit positive effects on plant growth and biomass yield. However, the actual mechanism behind the plant-PGPB interaction is poorly understood, and the literature is scarce regarding the thermochemical pretreatability and enzymatic degradability of biomass derived from PGPB-inoculated plants. Most recent transcriptional analyses of PGPB strain Burkholderia phytofirmans PsJN inoculating potato in literature and Arabidopsis in our present study have revealed the expression of genes for ferritin and the biosynthesis and transport of siderophores (i.e., the molecules with high affinity for iron), respectively. The expression of such genes in the shoots of PsJN-inoculated plants prompted us to propose that PsJN-inoculation can improve the host plant's iron uptake and accumulation, which facilitates the downstream plant biomass pretreatment and conversion to simple sugars. In this study, we employed B. phytofirmans PsJN to inoculate the Arabidopsis thaliana plants, and conducted the first investigation for its effects on the biomass yield, the anatomical organization of stems, the iron accumulation, and the pretreatment and enzymatic hydrolysis of harvested biomass. The results showed that the strain PsJN stimulated plant growth in the earlier period of plant development and enlarged the cell size of stem piths, and it also indeed enhanced the essential metals uptake and accumulation in host plants. Moreover, we found that the PsJN-inoculated plant biomass released more glucose and xylose after hot water pretreatment and subsequent co-saccharification, which provided a novel insight into development of lignocellulosic biofuels from renewable biomass resources.

Identifying the ionically bound cell wall and intracellular glycoside hydrolases in late growth stage Arabidopsis stems: implications for the genetic engineering of bioenergy crops

Identifying the cell wall-ionically bound glycoside hydrolases (GHs) in Arabidopsis stems is important for understanding the regulation of cell wall integrity. For cell wall proteomics studies, the preparation of clean cell wall fractions is a challenge since cell walls constitute an open compartment, which is more likely to contain a mixture of intracellular and extracellular proteins due to cell leakage at the late growth stage. Here, we utilize a CaCl2-extraction procedure to isolate non-structural proteins from Arabidopsis whole stems, followed by the in-solution and in-gel digestion methods coupled with Nano-LC-MS/MS, bioinformatics and literature analyses. This has led to the identification of 75 proteins identified using the in-solution method and 236 proteins identified by the in-gel method, among which about 10% of proteins predicted to be secreted. Together, eight cell wall proteins, namely AT1G75040, AT5G26000, AT3G57260, AT4G21650, AT3G52960, AT3G49120, AT5G49360, and AT3G14067, were identified by the in-solution method; among them, three were the GHs (AT5G26000, myrosinase 1, GH1; AT3G57260, β-1,3-glucanase 2, GH17; AT5G49360, bifunctional XYL 1/α-L-arabinofuranosidase, GH3). Moreover, four more GHs: AT4G30270 (xyloglucan endotransferase, GH16), AT1G68560 (bifunctional α-l-arabinofuranosidase/XYL, GH31), AT1G12240 (invertase, GH32) and AT2G28470 (β-galactosidase 8, GH35), were identified by the in-gel solution method only. Notably, more than half of above identified GHs are xylan- or hemicellulose-modifying enzymes, and will likely have an impact on cellulose accessibility, which is a critical factor for downstream enzymatic hydrolysis of plant tissues for biofuels production. The implications of these cell wall proteins identified at the late growth stage for the genetic engineering of bioenergy crops are discussed.