High Throughput Screening Technologies in Biomass Characterization

Biomass analysis is a slow and tedious process and not solely due to the long generation time for most plant species. Screening large numbers of plant variants for various geno-, pheno-, and chemotypes, whether naturally occurring or engineered in the lab, has multiple challenges. Plant cell walls are complex, heterogeneous networks that are difficult to deconstruct and analyze. Macroheterogeneity from tissue types, age, and environmental factors makes representative sampling a challenge and natural variability generates a significant range in data. Using high throughput (HTP) methodologies allows for large sample sets and replicates to be examined, narrowing in on more precise data for various analyses. This review provides a comprehensive survey of high throughput screening as applied to biomass characterization, from compositional analysis of cell walls by NIR, NMR, mass spectrometry, and wet chemistry to functional screening of changes in recalcitrance via HTP thermochemical pretreatment coupled to enzyme hydrolysis and microscale fermentation. The advancements and development of most high-throughput methods have been achieved through utilization of state-of-the art equipment and robotics, rapid detection methods, as well as reduction in sample size and preparation procedures. The computational analysis of the large amount of data generated using high throughput analytical techniques has recently become more sophisticated, faster and economically viable, enabling a more comprehensive understanding of biomass genomics, structure, composition and properties. Therefore, methodology for analyzing large datasets generated by the various analytical techniques is also covered.

[1]  Mark F. Davis,et al.  ORIGINAL RESEARCH: Lignocellulose recalcitrance screening by integrated high-throughput hydrothermal pretreatment and enzymatic saccharification , 2010 .

[2]  Claire Halpin,et al.  Automated saccharification assay for determination of digestibility in plant materials , 2010, Biotechnology for biofuels.

[3]  Zili Yi,et al.  Biomass properties from different Miscanthus species. , 2013 .

[4]  M. Studer,et al.  Small‐scale and automatable high‐throughput compositional analysis of biomass , 2011, Biotechnology and bioengineering.

[5]  Bruce E Dale,et al.  High-throughput microplate technique for enzymatic hydrolysis of lignocellulosic biomass. , 2008, Biotechnology and bioengineering.

[6]  Jo Dicks,et al.  Methodology for enabling high-throughput simultaneous saccharification and fermentation screening of yeast using solid biomass as a substrate , 2015, Biotechnology for Biofuels.

[7]  Shahab Sokhansanj,et al.  Variation in corn stover composition and energy content with crop maturity , 2005 .

[8]  David W. Templeton,et al.  Rapid biomass analysis , 2003 .

[9]  Pascal Dhulster,et al.  High-throughput fermentation screening for the yeast Yarrowia lipolytica with real-time monitoring of biomass and lipid production , 2016, Microbial Cell Factories.

[10]  David W. Templeton,et al.  Compositional Analysis of Lignocellulosic Feedstocks. 1. Review and Description of Methods , 2010, Journal of agricultural and food chemistry.

[11]  J. Shenk,et al.  Determination of Forage Quality by near Infrared Reflectance Spectroscopy: Efficacy of Broad-Based Calibration Equations, , , , 1987 .

[12]  Ewa M. Bielihska,et al.  COMPARISON OF DIFFERENT METHODS , 1994 .

[13]  David W. Templeton,et al.  Assessing corn stover composition and sources of variability via NIRS , 2009 .

[14]  Yankun Yang,et al.  The development and application of high throughput cultivation technology in bioprocess development. , 2014, Journal of biotechnology.

[15]  M. Pauly,et al.  A High-Throughput Platform for Screening Milligram Quantities of Plant Biomass for Lignocellulose Digestibility , 2010, BioEnergy Research.

[16]  E. Keshavarz‐Moore,et al.  High throughput automated microbial bioreactor system used for clone selection and rapid scale‐down process optimization , 2017, Biotechnology progress.

[17]  W. J. Dyer,et al.  A rapid method of total lipid extraction and purification. , 1959, Canadian journal of biochemistry and physiology.

[18]  Bruno Godin,et al.  Composition of structural carbohydrates in biomass: precision of a liquid chromatography method using a neutral detergent extraction and a charged aerosol detector. , 2011, Talanta.

[19]  Jochen Büchs,et al.  Microscale and miniscale fermentation and screening. , 2015, Current opinion in biotechnology.

[20]  Tianyong Zheng,et al.  Simultaneous achievement of high ethanol yield and titer in Clostridium thermocellum , 2016, Biotechnology for Biofuels.

[21]  A. Barabasi,et al.  Network biology: understanding the cell's functional organization , 2004, Nature Reviews Genetics.

[22]  Ajaya K. Biswal,et al.  Downregulation of GAUT12 in Populus deltoides by RNA silencing results in reduced recalcitrance, increased growth and reduced xylan and pectin in a woody biofuel feedstock , 2015, Biotechnology for Biofuels.

[23]  K. Waldron Bioalcohol production : biochemical conversion of lignocellulosic biomass , 2010 .

[24]  Mark F. Davis,et al.  Lignin content in natural Populus variants affects sugar release , 2011, Proceedings of the National Academy of Sciences.

[25]  Marco G. Casteleijn,et al.  Expression without boundaries: cell-free protein synthesis in pharmaceutical research. , 2013, International journal of pharmaceutics.

[26]  A. Kondo,et al.  Biodiesel fuel production by transesterification of oils. , 2001, Journal of bioscience and bioengineering.

[27]  Stephen R. Decker,et al.  High throughput determination of glucan and xylan fractions in lignocelluloses , 2011, Biotechnology Letters.

[28]  Mark F. Davis,et al.  Characterization and enzymatic hydrolysis of wood from transgenic Pinus taeda engineered with syringyl lignin or reduced lignin content , 2017, Cellulose.

[29]  Matt A. Sanderson,et al.  Compositional analysis of biomass feedstocks by near infrared reflectance spectroscopy , 1996 .

[30]  A. Korte,et al.  The advantages and limitations of trait analysis with GWAS: a review , 2013, Plant Methods.

[31]  Gary M. Scott,et al.  Quantitative analysis of sugars in wood hydrolyzates with 1H NMR during the autohydrolysis of hardwoods. , 2009, Bioresource technology.

[32]  Mark F. Davis,et al.  Genetic Determinants for Enzymatic Digestion of Lignocellulosic Biomass Are Independent of Those for Lignin Abundance in a Maize Recombinant Inbred Population1[W][OPEN] , 2014, Plant Physiology.

[33]  Mark F. Davis,et al.  Estimation of terpene content in loblolly pine biomass using a hybrid fast-GC and pyrolysis-molecular beam mass spectrometry method , 2017 .

[34]  Stephen R. Decker,et al.  High-Throughput Screening Techniques for Biomass Conversion , 2009, BioEnergy Research.

[35]  M. Wagner,et al.  A robust high-throughput fungal biosensor assay for the detection of estrogen activity , 2017, Steroids.

[37]  Jerry Workman,et al.  A Review of Calibration Transfer Practices and Instrument Differences in Spectroscopy , 2018, Applied spectroscopy.

[38]  Charles E Wyman,et al.  Rapid selection and identification of Miscanthus genotypes with enhanced glucan and xylan yields from hydrothermal pretreatment followed by enzymatic hydrolysis , 2012, Biotechnology for Biofuels.

[39]  E. Dahlquist,et al.  Applications of near-infrared spectroscopy (NIRS) in biomass energy conversion processes: A review , 2017 .

[40]  Wayne Joubert,et al.  Parallel Accelerated Vector Similarity Calculations for Genomics Applications , 2017, Parallel Comput..

[41]  Salvador García-Muñoz,et al.  A comparison of different methods to estimate prediction uncertainty using Partial Least Squares (PLS): A practitioner's perspective , 2009 .

[42]  M. Spraul,et al.  Mixture analysis by NMR as applied to fruit juice quality control , 2009, Magnetic resonance in chemistry : MRC.

[43]  Mark F. Davis,et al.  Within tree variability of lignin composition in Populus , 2008, Wood Science and Technology.

[44]  Karsten Rebner,et al.  Hyperspectral Imaging: A Review of Best Practice, Performance and Pitfalls for in-line and on-line Applications , 2012 .

[45]  Mark F. Davis,et al.  Down-regulation of p-coumaroyl quinate/shikimate 3′-hydroxylase (C3′H) and cinnamate 4-hydroxylase (C4H) genes in the lignin biosynthetic pathway of Eucalyptus urophylla × E. grandis leads to improved sugar release , 2015, Biotechnology for Biofuels.

[46]  G. Pereira,et al.  Determination of metabolite profiles in tropical wines by 1H NMR spectroscopy and chemometrics , 2009, Magnetic resonance in chemistry : MRC.

[47]  Y. Chisti Biodiesel from microalgae. , 2007, Biotechnology advances.

[48]  H. Kang,et al.  Variance component model to account for sample structure in genome-wide association studies , 2010, Nature Genetics.

[49]  J. Nielsen,et al.  Engineering central metabolism – a grand challenge for plant biologists , 2017, The Plant journal : for cell and molecular biology.

[50]  David Jameson,et al.  Fluorescent measurement of microalgal neutral lipids. , 2007, Journal of microbiological methods.

[51]  N. M. Faber,et al.  Uncertainty estimation and figures of merit for multivariate calibration (IUPAC Technical Report) , 2006 .

[52]  M. Poenie,et al.  Extraction of Algal Lipids and Their Analysis by HPLC and Mass Spectrometry , 2012 .

[53]  M. Studer,et al.  Engineering of a high‐throughput screening system to identify cellulosic biomass, pretreatments, and enzyme formulations that enhance sugar release , 2010, Biotechnology and bioengineering.

[54]  Sharlee Climer,et al.  A Custom Correlation Coefficient (CCC) Approach for Fast Identification of Multi‐SNP Association Patterns in Genome‐Wide SNPs Data , 2014, Genetic epidemiology.

[55]  Charles K. Bayne,et al.  Multivariate Analysis of Quality: An Introduction , 2002, Technometrics.

[56]  High-throughput enzymatic hydrolysis of lignocellulosic biomass via in-situ regeneration. , 2011, Bioresource technology.

[57]  Robert W. Sykes,et al.  High-resolution genetic mapping of allelic variants associated with cell wall chemistry in Populus , 2015, BMC Genomics.

[58]  K. Foster,et al.  The evolution of the host microbiome as an ecosystem on a leash , 2017, Nature.

[59]  R. Withers,et al.  Low-conductivity buffers for high-sensitivity NMR measurements. , 2002, Journal of the American Chemical Society.

[60]  Amie D. Sluiter,et al.  Near Infrared Calibration Models for Pretreated Corn Stover Slurry Solids, Isolated and in situ , 2013 .

[61]  C. X. Sun,et al.  Metabolic response of maize plants to multi-factorial abiotic stresses. , 2016, Plant biology.

[62]  Michael E Himmel,et al.  Automated filter paper assay for determination of cellulase activity. , 2003, Applied biochemistry and biotechnology.

[63]  Amie D. Sluiter,et al.  Improved multivariate calibration models for corn stover feedstock and dilute-acid pretreated corn stover , 2009 .

[64]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[65]  C. Franceschi,et al.  High-Resolution Quantitative Metabolome Analysis of Urine by Automated Flow Injection NMR , 2013, Analytical chemistry.

[66]  E. Baldoni,et al.  NMR techniques coupled with multivariate statistical analysis: tools to analyse Oryza sativa metabolic content under stress conditions. , 2009 .

[67]  Tina Lütke-Eversloh,et al.  New options to engineer biofuel microbes: development and application of a high-throughput screening system. , 2013, Metabolic engineering.

[68]  J. Shenk,et al.  Predicting Forage Quality by Infrared Replectance Spectroscopy , 1976 .

[69]  T. K. Ghose Measurement of cellulase activities , 1987 .

[70]  R. Wijffels,et al.  An Outlook on Microalgal Biofuels , 2010, Science.

[71]  Xiaolan Yang,et al.  High-throughput estimation of specific activities of enzyme/mutants in cell lysates through immunoturbidimetric assay of proteins. , 2017, Analytical biochemistry.

[72]  E. Buckler,et al.  Structure of linkage disequilibrium in plants. , 2003, Annual review of plant biology.

[73]  I. Sakata,et al.  A high-throughput direct fluorescence resonance energy transfer-based assay for analyzing apoptotic proteases using flow cytometry and fluorescence lifetime measurements. , 2015, Analytical biochemistry.

[74]  J. Saddler,et al.  A rapid microassay to evaluate enzymatic hydrolysis of lignocellulosic substrates , 2006, Biotechnology and bioengineering.

[75]  F. Fauvelle,et al.  Effect of organochlorine pesticides exposure on the maize root metabolome assessed using high-resolution magic-angle spinning (1)H NMR spectroscopy. , 2016, Environmental pollution.

[76]  L. Barantin,et al.  Concentration Measurement by Proton NMR Using the ERETIC Method. , 1999, Analytical chemistry.

[77]  A. Fontana,et al.  Composition and Quantitation of Microalgal Lipids by ERETIC 1H NMR Method , 2013, Marine drugs.

[78]  B. Davison,et al.  Consolidated bioprocessing of transgenic switchgrass by an engineered and evolved Clostridium thermocellum strain , 2014, Biotechnology for Biofuels.

[79]  M. Pauly,et al.  Comprehensive Compositional Analysis of Plant Cell Walls (Lignocellulosic biomass) Part II: Carbohydrates , 2010, Journal of Visualized Experiments.

[80]  Ajaya K. Biswal,et al.  Sugar release and growth of biofuel crops are improved by downregulation of pectin biosynthesis , 2018, Nature Biotechnology.

[81]  E. Wolfrum,et al.  Rapid analysis of composition and reactivity in cellulosic biomass feedstocks with near-infrared spectroscopy , 2015, Biotechnology for Biofuels.

[82]  C. Wyman,et al.  Evaluation of high throughput screening methods in picking up differences between cultivars of lignocellulosic biomass for ethanol production , 2014 .

[83]  A. Stipanovic,et al.  Proton NMR Methods in the Compositional Characterization of Polysaccharides , 2003 .

[84]  Robert W. Sykes,et al.  Consolidated bioprocessing of Populus using Clostridium (Ruminiclostridium) thermocellum: a case study on the impact of lignin composition and structure , 2016, Biotechnology for Biofuels.

[85]  Wei Chen,et al.  A high throughput Nile red method for quantitative measurement of neutral lipids in microalgae. , 2009, Journal of microbiological methods.

[86]  J. A. Teixeira da Silva,et al.  Metabolomics: Creating new potentials for unraveling the mechanisms in response to salt and drought stress and for the biotechnological improvement of xero-halophytes , 2011, Critical reviews in biotechnology.

[87]  C. N. Stewart,et al.  Rapid Assessment of Lignin Content and Structure in Switchgrass (Panicum virgatum L.) Grown Under Different Environmental Conditions , 2009, BioEnergy Research.

[88]  Vincent Baeten,et al.  NIR hyperspectral imaging spectroscopy and chemometrics for the discrimination of roots and crop residues extracted from soil samples , 2018 .

[89]  Jonathan R Mielenz,et al.  Evaluation of the bioconversion of genetically modified switchgrass using simultaneous saccharification and fermentation and a consolidated bioprocessing approach , 2012, Biotechnology for Biofuels.

[90]  S. Purcell,et al.  Pleiotropy in complex traits: challenges and strategies , 2013, Nature Reviews Genetics.

[91]  Mark F. Davis,et al.  High-Throughput Method for Determining the Sugar Content in Biomass with Pyrolysis Molecular Beam Mass Spectrometry , 2015, BioEnergy Research.

[92]  P. Visscher,et al.  Five years of GWAS discovery. , 2012, American journal of human genetics.

[93]  Philip T. Pienkos,et al.  Role of pretreatment and conditioning processes on toxicity of lignocellulosic biomass hydrolysates , 2009 .

[94]  Malia A. Gehan,et al.  Lights, camera, action: high-throughput plant phenotyping is ready for a close-up. , 2015, Current opinion in plant biology.

[95]  Mark F. Davis,et al.  High-throughput Screening of Recalcitrance Variations in Lignocellulosic Biomass: Total Lignin, Lignin Monomers, and Enzymatic Sugar Release. , 2015, Journal of visualized experiments : JoVE.

[96]  Patrik R. Callis,et al.  Fluorometric determination of the neutral lipid content of microalgal cells using Nile Red , 1987 .

[97]  Hui Li,et al.  High-throughput protein purification and quality assessment for crystallization. , 2011, Methods.

[98]  Mark F. Davis,et al.  Association genetics of traits controlling lignin and cellulose biosynthesis in black cottonwood (Populus trichocarpa, Salicaceae) secondary xylem. , 2010, The New phytologist.

[99]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[100]  M. Himmel,et al.  NIR and Py-mbms coupled with multivariate data analysis as a high-throughput biomass characterization technique: a review , 2014, Front. Plant Sci..

[101]  Mark F. Davis,et al.  Reducing the effect of variable starch levels in biomass recalcitrance screening. , 2012, Methods in molecular biology.

[102]  Amie D. Sluiter,et al.  Rapid biomass analysis , 2003, Applied biochemistry and biotechnology.

[103]  Mark F. Davis,et al.  Rapid determination of sugar content in biomass hydrolysates using nuclear magnetic resonance spectroscopy , 2013, Biotechnology and bioengineering.

[104]  S. Akoka,et al.  Strategy for choosing extraction procedures for NMR-based metabolomic analysis of mammalian cells , 2011, Analytical and bioanalytical chemistry.

[105]  B. Davison,et al.  Anaerobic microplate assay for direct microbial conversion of switchgrass and Avicel using Clostridium thermocellum , 2017, Biotechnology Letters.

[106]  J. Shenk,et al.  Analysis of Forages by Infrared Reflectance , 1979 .

[107]  J. Peñuelas,et al.  Ecometabolomics: optimized NMR‐based method , 2013 .

[108]  Christophe Ley,et al.  Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the median , 2013 .

[109]  C. Howe,et al.  Biodiesel from algae: challenges and prospects. , 2010, Current opinion in biotechnology.

[110]  H. Martens,et al.  Multivariate analysis of quality , 2000 .

[111]  Mark F. Davis,et al.  Validation of PyMBMS as a High-throughput Screen for Lignin Abundance in Lignocellulosic Biomass of Grasses , 2014, BioEnergy Research.

[112]  R. Powers NMR metabolomics and drug discovery , 2009, Magnetic resonance in chemistry : MRC.