Combining multivariate analysis and monosaccharide composition modeling to identify plant cell wall variations by Fourier Transform Near Infrared spectroscopy

The Potential Use of Near- and Mid-Infrared Spectroscopy in Kidney Diseases

Traditional renal biomarkers such as serum creatinine and albuminuria/proteinuria are rather insensitive since they change later in the course of the disease. In order to determine the extent and type of kidney injury, as well as to administer the proper therapy and enhance patient management, new techniques for the detection of deterioration of the kidney function are urgently needed. Infrared spectroscopy is a label-free and non-destructive technique having the potential to be a vital tool for quick and inexpensive routine clinical diagnosis of kidney disorders. The aim of this review is to provide an overview of near- and mid-infrared spectroscopy applications in patients with acute kidney injury and chronic kidney disease (e.g., diabetic nephropathy and glomerulonephritis).

Authenticity identification and classification of Rhodiola species in traditional Tibetan medicine based on Fourier transform near-infrared spectroscopy and chemometrics analysis

Rhodiola is an increasingly widely used traditional Tibetan medicine and traditional Chinese medicine in China. The composition profiles of bioactive compounds are somewhat jagged according to different species, which makes it crucial to identify authentic Rhodiola species accurately so as to ensure clinical application of Rhodiola. In this paper, a nondestructive, rapid, and efficient method in classification of Rhodiola was developed by Fourier transform near-infrared (FT-NIR) spectroscopy combined with chemometrics analysis. A total of 160 batches of raw spectra were obtained from four different species of Rhodiola by FT-NIR, such as Rhodiola crenulata, Rhodiola fastigiata, Rhodiola kirilowii, and Rhodiola brevipetiolata. After excluding the outliers, different performances of 3 sample dividing methods, 12 spectral preprocessing methods, 2 wavelength selection methods, and 2 modeling evaluation methods were compared. The results indicated that this combination was superior than others in the authenticity identification analysis, which was FT-NIR combined with sample set partitioning based on joint x-y distances (SPXY), standard normal variate transformation (SNV) + Norris-Williams (NW) + 2nd derivative, competitive adaptive reweighted sampling (CARS), and kernel extreme learning machine (KELM). The accuracy (ACCU), sensitivity (SENS), and specificity (SPEC) of the optimal model were all 1, which showed that this combination of FT-NIR and chemometrics methods had the optimal authenticity identification performance. The classification performance of the partial least squares discriminant analysis (PLS-DA) model was slightly lower than KELM model, and PLS-DA model results were ACCU = 0.97, SENS = 0.93, and SPEC = 0.98, respectively. It can be concluded that FT-NIR combined with chemometrics analysis has great potential in authenticity identification and classification of Rhodiola, which can provide a valuable reference for the safety and effectiveness of clinical application of Rhodiola.

Logistics of Lignocellulosic Feedstocks: Preprocessing as a Preferable Option

In comparison to crude oil, biorefinery raw materials are challenging in concerns of transport and storage. The plant raw materials are more voluminous, so that shredding and compacting usually are necessary before transport. These mechanical processes can have a negative influence on the subsequent biotechnological processing and shelf life of the raw materials. Various approaches and their effects on renewable raw materials are shown. In addition, aspects of decentralized pretreatment steps are discussed. Another important aspect of pretreatment is the varying composition of the raw materials depending on the growth conditions. This problem can be solved with advanced on-site spectrometric analysis of the material. Graphical Abstract.

A Review of Mid-Infrared and Near-Infrared Imaging: Principles, Concepts and Applications in Plant Tissue Analysis

Plant cells, tissues and organs are composed of various biomolecules arranged as structurally diverse units, which represent heterogeneity at microscopic levels. Molecular knowledge about those constituents with their localization in such complexity is very crucial for both basic and applied plant sciences. In this context, infrared imaging techniques have advantages over conventional methods to investigate heterogeneous plant structures in providing quantitative and qualitative analyses with spatial distribution of the components. Thus, particularly, with the use of proper analytical approaches and sampling methods, these technologies offer significant information for the studies on plant classification, physiology, ecology, genetics, pathology and other related disciplines. This review aims to present a general perspective about near-infrared and mid-infrared imaging/microspectroscopy in plant research. It is addressed to compare potentialities of these methodologies with their advantages and limitations. With regard to the organization of the document, the first section will introduce the respective underlying principles followed by instrumentation, sampling techniques, sample preparations, measurement, and an overview of spectral pre-processing and multivariate analysis. The last section will review selected applications in the literature.

A precise and consistent assay for major wall polymer features that distinctively determine biomass saccharification in transgenic rice by near-infrared spectroscopy

BACKGROUND

The genetic modification of plant cell walls has been considered to reduce lignocellulose recalcitrance in bioenergy crops. As a result, it is important to develop a precise and rapid assay for the major wall polymer features that affect biomass saccharification in a large population of transgenic plants. In this study, we collected a total of 246 transgenic rice plants that, respectively, over-expressed and RNAi silenced 12 genes of the OsGH9 and OsGH10 family that are closely associated with cellulose and hemicellulose modification. We examined the wall polymer features and biomass saccharification among 246 transgenic plants and one wild-type plant. The samples presented a normal distribution applicable for statistical analysis and NIRS modeling.

RESULTS

Among the 246 transgenic rice plants, we determined largely varied wall polymer features and the biomass enzymatic saccharification after alkali pretreatment in rice straws, particularly for the fermentable hexoses, ranging from 52.8 to 95.9%. Correlation analysis indicated that crystalline cellulose and lignin levels negatively affected the hexose and total sugar yields released from pretreatment and enzymatic hydrolysis in the transgenic rice plants, whereas the arabinose levels and arabinose substitution degree (reverse xylose/arabinose ratio) exhibited positive impacts on the hexose and total sugars yields. Notably, near-infrared spectroscopy (NIRS) was applied to obtain ten equations for predicting biomass enzymatic saccharification and seven equations for distinguishing major wall polymer features. Most of the equations exhibited high R²/R²_cv/R²_ev and RPD values for a perfect prediction capacity.

CONCLUSIONS

Due to large generated populations of transgenic rice lines, this study has not only examined the key wall polymer features that distinctively affect biomass enzymatic saccharification in rice but has also established optimal NIRS models for a rapid and precise screening of major wall polymer features and lignocellulose saccharification in biomass samples. Importantly, this study has briefly explored the potential roles of a total of 12 OsGH9 and OsGH10 genes in cellulose and hemicellulose modification and cell wall remodeling in transgenic rice lines. Hence, it provides a strategy for genetic modification of plant cell walls by expressing the desired OsGH9 and OsGH10 genes that could greatly improve biomass enzymatic digestibility in rice.

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

Optimizing the use of lignocellulosic biomass as the feedstock for renewable energy production is currently being developed globally. Biomass is a complex mixture of cellulose, hemicelluloses, lignins, extractives, and proteins; as well as inorganic salts. Cell wall compositional analysis for biomass characterization is laborious and time consuming. In order to characterize biomass fast and efficiently, several high through-put technologies have been successfully developed. Among them, near infrared spectroscopy (NIR) and pyrolysis-molecular beam mass spectrometry (Py-mbms) are complementary tools and capable of evaluating a large number of raw or modified biomass in a short period of time. NIR shows vibrations associated with specific chemical structures whereas Py-mbms depicts the full range of fragments from the decomposition of biomass. Both NIR vibrations and Py-mbms peaks are assigned to possible chemical functional groups and molecular structures. They provide complementary information of chemical insight of biomaterials. However, it is challenging to interpret the informative results because of the large amount of overlapping bands or decomposition fragments contained in the spectra. In order to improve the efficiency of data analysis, multivariate analysis tools have been adapted to define the significant correlations among data variables, so that the large number of bands/peaks could be replaced by a small number of reconstructed variables representing original variation. Reconstructed data variables are used for sample comparison (principal component analysis) and for building regression models (partial least square regression) between biomass chemical structures and properties of interests. In this review, the important biomass chemical structures measured by NIR and Py-mbms are summarized. The advantages and disadvantages of conventional data analysis methods and multivariate data analysis methods are introduced, compared and evaluated. This review aims to serve as a guide for choosing the most effective data analysis methods for NIR and Py-mbms characterization of biomass.

Fourier transform mid infrared spectroscopy applications for monitoring the structural plasticity of plant cell walls

Fourier transform mid-infrared (FT-MIR) spectroscopy has been extensively used as a potent, fast and non-destructive procedure for analyzing cell wall architectures, with the capacity to provide abundant information about their polymers, functional groups, and in muro entanglement. In conjunction with multivariate analyses, this method has proved to be a valuable tool for tracking alterations in cell walls. The present review examines recent progress in the use of FT-MIR spectroscopy to monitor cell wall changes occurring in muro as a result of various factors, such as growth and development processes, genetic modifications, exposition or habituation to cellulose biosynthesis inhibitors and responses to other abiotic or biotic stresses, as well as its biotechnological applications.

Analysis of plant nucleotide sugars by hydrophilic interaction liquid chromatography and tandem mass spectrometry

Understanding the intricate metabolic processes involved in plant cell wall biosynthesis is limited by difficulties in performing sensitive quantification of many involved compounds. Hydrophilic interaction liquid chromatography is a useful technique for the analysis of hydrophilic metabolites from complex biological extracts and forms the basis of this method to quantify plant cell wall precursors. A zwitterionic silica-based stationary phase has been used to separate hydrophilic nucleotide sugars involved in cell wall biosynthesis from milligram amounts of leaf tissue. A tandem mass spectrometry operating in selected reaction monitoring mode was used to quantify nucleotide sugars. This method was highly repeatable and quantified 12 nucleotide sugars at low femtomole quantities, with linear responses up to four orders of magnitude to several 100pmol. The method was also successfully applied to the analysis of purified leaf extracts from two model plant species with variations in their cell wall sugar compositions and indicated significant differences in the levels of 6 out of 12 nucleotide sugars. The plant nucleotide sugar extraction procedure was demonstrated to have good recovery rates with minimal matrix effects. The approach results in a significant improvement in sensitivity when applied to plant samples over currently employed techniques.

Callose and cellulose synthase gene expression analysis from the tight cluster to the full bloom stage and during early fruit development in Malus × domestica

Apple (Malus × domestica) is an economically important temperate fruit-bearing crop which belongs to the family of Rosaceae and its pomaceous fruit is one of the most commonly cultivated. Several studies have demonstrated that the cell wall plays a pivotal role during flower and fruit development. It takes active part in pollen tube growth and contributes to determine the fruit firmness trait through the action of cell wall-related enzymes (i.e. polygalacturonase and pectinmethylesterase). We have investigated the expression of callose and cellulose synthase genes during flowering from tight cluster to anthesis and during early fruit development in domesticated apple. We also link the changes observed in gene expression to the profile of soluble non-structural carbohydrates at different developmental stages of flowers/fruitlets and to the qualitative results linked to wall polysaccharides' composition obtained through near-infrared spectroscopy. This work represents an important addition to the study of tree physiology with respect to the analysis of the expression of callose and cellulose synthase genes during flower and early fruit development in domesticated apple.

Structural and chemical characterization of hardwood from tree species with applications as bioenergy feedstocks

Eucalypt species are a group of flowering trees widely used in pulp production for paper manufacture. For several decades, the wood pulp industry has focused research and development efforts on improving yields, growth rates and pulp quality through breeding and the genetic improvement of key tree species. Recently, this focus has shifted from the production of high quality pulps to the investigation of the use of eucalypts as feedstocks for biofuel production. Here the structure and chemical composition of the heartwood and sapwood of Eucalyptus dunnii, E. globulus, E. pillularis, E. urophylla, an E. urophylla-E. grandis cross, Corymbia citriodora ssp. variegata, and Acacia mangium were compared using nuclear magnetic resonance spectroscopy (NMR), X-ray diffraction (XRD) and biochemical composition analysis. Some trends relating to these compositions were also identified by Fourier transform near infrared (FT-NIR) spectroscopy. These results will serve as a foundation for a more comprehensive database of wood properties that will help develop criteria for the selection of tree species for use as biorefinery feedstocks.

AtAPY1 and AtAPY2 function as Golgi-localized nucleoside diphosphatases in Arabidopsis thaliana

Nucleoside triphosphate diphosphohydrolases (NTPDases; apyrases) (EC 3.6.1.5) hydrolyze di- and triphosphate nucleotides, but not monophosphate nucleotides. They are categorized as E-type ATPases, have a broad divalent cation (Mg(2+), Ca(2+)) requirement for activation and are insensitive to inhibitors of F-type, P-type and V-type ATPases. Among the seven NTPDases identified in Arabidopsis, only APYRASE 1 (AtAPY1) and APYRASE 2 (AtAPY2) have been previously characterized. In this work, either AtAPY1 or AtAPY2 tagged with C-terminal green fluorescent protein (GFP) driven by their respective native promoter can rescue the apy1 apy2 double knockout (apy1 apy2 dKO) successfully, and confocal microscopy reveals that these two Arabidopsis apyrases reside in the Golgi apparatus. In Saccharomyces cerevisiae, both AtAPY1 and AtAPY2 can complement the Golgi-localized GDA1 mutant, rescuing its aberrant protein glycosylation phenotype. In Arabidopsis, microsomes of the wild type show higher substrate preferences toward UDP compared with other NDP substrates. Loss-of-function Arabidopsis AtAPY1 mutants exhibit reduced microsomal UDPase activity, and this activity is even more significantly reduced in the loss-of-function AtAPY2 mutant and in the AtAPY1/AtAPY2 RNA interference (RNAi) technology repressor lines. Microsomes from wild-type plants also have detectable GDPase activity, which is significantly reduced in apy2 but not apy1 mutants. The GFP-tagged AtAPY1 or AtAPY2 constructs in the apy1 apy2 dKO plants can restore microsomal UDP/GDPase activity, confirming that they both also have functional competency. The cell walls of apy1, apy2 and the RNAi-silenced lines all have an increased composition of galactose, but the transport efficiency of UDP-galactose across microsomal membranes was not altered. Taken together, these results reveal that AtAPY1 and AtAPY2 are Golgi-localized nucleotide diphosphatases and are likely to have roles in regulating UDP/GDP concentrations in the Golgi lumen.