Maltose Analysis Service

What is Maltose?

Maltose, commonly known as malt sugar, is a disaccharide composed of two glucose molecules linked together by an α(1→4) glycosidic bond. Its chemical formula is C₁₂H₂₂O₁₁, and it is part of a class of carbohydrates that play essential roles in various biological and industrial processes. Maltose is a reducing sugar, meaning it possesses a free aldehyde group that can donate electrons to other molecules, making it chemically reactive in certain conditions.

Maltose is vital in:

• Energy metabolism: In living organisms, maltose is broken down into glucose, then used for energy production.
• Brewing and fermentation: Maltose is a key fermentable sugar in brewing, as yeast converts it into alcohol and carbon dioxide during fermentation.
• Food and beverage industry: Maltose is used as a mild sweetener and moisture-retaining agent in baked goods, syrups, and confectioneries.
• Pharmaceuticals: It acts as a stabilizer in drug formulations, especially in protein-based therapies.

Due to its widespread applications in these fields, precise analysis of maltose levels is essential for ensuring product quality, optimizing processes, and enhancing scientific understanding.

Maltose Analysis Services Offered by Creative Proteomics

At Creative Proteomics, we provide a wide range of tailored maltose analysis services. Our solutions are designed to support industries, research institutions, and manufacturers who need precise quantification, characterization, and quality control of maltose content in various matrices. Key maltose analysis services we offer include:

Maltose Quantification

Quantification of maltose is crucial for industries such as brewing and pharmaceuticals, where precise sugar concentrations are necessary for process control and product consistency. Using state-of-the-art analytical methods, we provide:

• High-Performance Liquid Chromatography (HPLC) for high-resolution separation and accurate measurement of maltose.
• Enzymatic Assays that specifically target maltose, offering rapid and sensitive quantification.

Maltose Content Determination in Complex Matrices

Maltose is often found in complex mixtures such as food products, beverages, and biological samples. Our advanced extraction and separation techniques ensure accurate quantification even in these challenging matrices. We specialize in:

• Food and beverage analysis
• Fermentation broth and bioprocess samples
• Biological tissue and serum analysis

Enzymatic Hydrolysis Studies

Understanding maltose generation during enzymatic hydrolysis of starch or polysaccharides is essential for various research and industrial processes. We offer:

• Analysis of maltose formation during enzymatic digestion of carbohydrates.
• Support for optimizing enzymatic processes in industrial applications such as brewing and food production.

Carbohydrate Profiling

We provide comprehensive carbohydrate profiling services, including maltose analysis, to support the characterization of carbohydrate composition in samples such as:

• Cereals and grains
• Nutritional supplements
• Processed food products

Brochures

Metabolomics Services

We provide unbiased non-targeted metabolomics and precise targeted metabolomics services to unravel the secrets of biological processes.

Our untargeted approach identifies and screens for differential metabolites, which are confirmed by standard methods. Follow-up targeted metabolomics studies validate important findings and support biomarker development.

Download our brochure to learn more about our solutions.

Download

Brochures

Glycomics Services

Glycomics, the study of glycans and their roles in biological systems, is critical for understanding processes like glycosylation, immune recognition, and cell signaling. At Creative Proteomics, we offer advanced platforms such as high-resolution mass spectrometry, glycan microarrays, and glycoproteomics to provide precise glycan profiling and analysis.

For detailed insights into our glycomics solutions and methodologies, download our Glycomics Service Brochure and discover how we can support your research.

Download

Technology Platforms for Maltose Analysis

High-Performance Liquid Chromatography (HPLC)

HPLC is a widely used and highly effective technique for maltose separation and quantification. By combining a separation column with precise detection methods, HPLC ensures:

• High sensitivity and specificity for maltose detection.
• Quantitative accuracy even in complex matrices.
• Application to a wide range of samples, including beverages, biological fluids, and processed foods.

Gas Chromatography (GC)

For samples requiring volatile derivatives or complex mixtures, GC is an alternative powerful tool. Paired with appropriate sample preparation, it provides:

• Efficient separation of maltose in vaporized form.
• High resolution for maltose quantification in industrial and environmental samples.

Mass Spectrometry (MS)

When sensitivity is paramount, mass spectrometry provides unmatched accuracy and detection limits. Using LC-MS or GC-MS, we achieve:

• High-throughput maltose analysis.
• Structural characterization of maltose and related carbohydrates.
• Ultra-low detection limits, suitable for trace-level quantification in sensitive applications.

Sample Requirements for Maltose Analysis

Please ensure samples are properly labeled, stored, and shipped to maintain integrity for accurate maltose analysis.

Multiomics of a rice population identifies genes and genomic regions that bestow low glycemic index and high protein content

Journal: Proceedings of the National Academy of Sciences (PNAS)

Published: 2024

Background

The world faces a triple burden of malnutrition characterized by obesity, undernutrition, and hidden hunger, with diabetes being a leading contributor to global mortality. The study focuses on developing rice varieties with low glycemic index (GI) and high protein content (PC) to combat diabetes and protein deficiency, especially in Asia where rice is a staple food. By employing genomics and metabolomics techniques, the study aims to identify candidate genes and genomic regions that facilitate the development of rice lines with ultralow GI and high PC, providing a vital breeding resource for enhancing food and nutritional security.

Materials & Methods

1) Population Development:

An F2-derived F3 mapping population was developed through hybridization between Samba Mahsuri and IR36 amylose extender (IR36ae) lines, with subsequent self-pollination until the F6 generation.

2) Measurement of Amylose and Protein Content:

Amylose content (AC) and protein content (PC) were measured from milled rice samples. AC was determined using sodium hydroxide dispersion and iodine complex formation, while PC was measured with the Kjeldahl method using Continuous Flow Analyser.

3) In-vitro Glycemic Index (GI) and Resistance Starch Analysis:

Milled rice samples were subjected to an in vitro digestion protocol mimicking human digestion, using enzymes to determine GI and resistance starch content under controlled conditions.

4) DNA Isolation and Whole Genome Sequencing:

Genomic DNA was extracted, and whole-genome resequencing was performed on selected bulk sets, with sequencing conducted using Illumina platforms to identify key SNPs.

5) QTL Mapping and Association Analyses:

QTL mapping for AC and PC used composite interval mapping. Targeted association and epistatic interaction analyses were conducted using PLINK1.9 and EMMAX software, with networks visualized in Cytoscape.

6) Metabolomic Analysis:

Rice flour samples were processed for metabolomic analysis through homogenization, sonication, and LC-MS to identify metabolic differences between samples.

7) Mathematical Modeling and Statistical Analysis:

GI classifications were performed using machine learning models, optimized for accuracy, with metabolomic data analyzed via PCA and oPLS-DA for pathway enrichment.

8) Rice Protein Isolate and Amino Acid Quantification:

Proteins were extracted from rice samples using an alkali extraction method, with amino acid quantification conducted following hydrolysis and HPLC analysis.

9) CRISPR/Cas9 Vector Construction and Rice Transformation:

The sgRNA targeting OsSBEIIb's exon 15 was designed and inserted into a CRISPR-Cas9 vector. Rice transformation employed Agrobacterium tumefaciens with subsequent sequence confirmation to produce T0 plants.

Results

Identification of Genetic Regions:

A broad variation in amylose content (AC) was observed in the F3 population, with multiple QTLs identified that influence AC and protein content (PC). Notably, OsSBEIIb, a major gene modulating starch branching, was highlighted.

Several candidate genes related to carbohydrate and protein metabolism were identified, providing targets for breeding rice with low glycemic index (GI) and high PC.

Trait Development through Gene Combination:

Ultralow GI, high AC, and high PC phenotypes were confirmed in advanced breeding lines through QTL analysis and targeted association studies.

Key alleles and SNPs contributing to phenotypic variance for GI, AC, and PC were discovered, highlighting the significance of OsSBEIIb in these traits.

Metabolomics Analysis:

Metabolomic profiles revealed significant differences between high AC/PC and low AC/PC lines, with amino acid and lipid metabolism pathways being particularly crucial.

In the ultralow GI samples, sugars like maltose, glucuronic acid, erythrose, and erythritol were significantly elevated, indicating distinct metabolic pathways among different GI classes.

Metabolomic analysis of HAHP and LALP groups.

Modeling and metabolomic analysis of ultralow, low, and high GI rice lines.

Machine Learning Classification:

Machine learning models effectively classified ultralow, low, and high GI classes based on AC, PC, and specific SNPs, offering robust tools for GI classification.

Enriched pathways for amino acid and flavonoid biosynthesis in the ultralow GI varieties underscore their potential relevance in differentiating GI levels.

CRISPR/Cas9-Mediated OsSBEIIb Mutagenesis:

OsSBEIIb was validated as a crucial gene influencing GI through CRISPR/Cas9-induced mutagenesis, resulting in lines with significantly reduced GI and increased resistant starch.

These mutant lines will undergo further testing and hold potential for development into rice varieties suitable for consumption.

Reference

1. Badoni, Saurabh, et al. "Multiomics of a rice population identifies genes and genomic regions that bestow low glycemic index and high protein content." Proceedings of the National Academy of Sciences 121.36 (2024): e2410598121.