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What is Malic Acid?
Malic acid is a naturally occurring organic compound that plays a pivotal role in various biochemical processes, particularly in the citric acid cycle (Krebs cycle), where it contributes to cellular energy production. Found abundantly in fruits like apples, cherries, and grapes, malic acid imparts the tart taste often associated with these foods, making it a critical ingredient in the food and beverage industry. Its presence is essential not only for flavor but also for maintaining product stability, acidity, and freshness.
In addition to its role in food products, malic acid is widely used across a broad spectrum of industries. In pharmaceuticals, it acts as a pH regulator and enhances the bioavailability of active ingredients. In cosmetics, malic acid is valued for its exfoliating properties, often incorporated into anti-aging creams and skin treatments to promote cell renewal and smooth skin texture. Furthermore, malic acid is increasingly being studied in biological research, as its concentration in tissues and fluids can be an indicator of metabolic activity and health conditions.
Given its widespread application and importance, precise and reliable analysis of malic acid content is crucial for quality control, regulatory compliance, and product development. Whether you are optimizing the taste and stability of a beverage, ensuring the therapeutic efficacy of a drug, or formulating a safe cosmetic product, accurate malic acid measurement is essential to achieving desired outcomes.
At Creative Proteomics, we offer metabolomics services designed to meet the specific needs of various industries. Using advanced analytical techniques and platforms, we ensure the highest levels of accuracy and reliability in malic acid quantification. Whether you're in food and beverage, pharmaceuticals, cosmetics, or biological research, our services can help you maintain product quality, optimize formulations, and meet industry standards with confidence.
Malic Acid Test in Creative Proteomics
Biological Sample Analysis: For research and diagnostic purposes, we quantify malic acid in biological samples like blood and tissue extracts, providing insights into metabolic health and disease.
Food and Beverage Analysis: We offer precise measurement of malic acid levels to ensure optimal flavor, acidity, and shelf life in products such as juices, wines, and soft drinks.
Pharmaceutical and Nutraceutical Analysis: Our analysis ensures the correct dosage and purity of malic acid, helping companies meet pharmacopoeial standards and regulatory requirements.
Cosmetics and Personal Care Products: We support cosmetic companies by ensuring accurate malic acid concentrations in products, vital for efficacy and safety, particularly in exfoliating and skin care formulas.
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.
Technology Platforms Used for Malic Acid Analysis
High-Performance Liquid Chromatography (HPLC)
Our Agilent 1260 Infinity II HPLC system is ideal for the precise quantification of malic acid, especially in complex matrices like food products, beverages, and biological samples. HPLC provides high sensitivity, excellent resolution, and reproducibility, making it the go-to technique for accurate malic acid measurement across various industries.
Gas Chromatography-Mass Spectrometry (GC-MS)
For enhanced specificity and isomer separation, we utilize the Agilent 7890B GC system coupled with the 5977B MS detector. This combination enables both quantification and identification of malic acid isomers, ensuring detailed profiling for high-complexity samples such as pharmaceutical formulations and biological extracts.
Liquid Chromatography-Mass Spectrometry (LC-MS)
The Thermo Scientific Q Exactive™ Orbitrap LC-MS system offers unparalleled sensitivity and accuracy, particularly for detecting trace levels of malic acid in biological or environmental samples. This platform is ideal for research applications that require detection of low-concentration metabolites.
Sample Requirements for Malic Acid Analysis
| Sample Type | Form | Required Amount | Storage Conditions |
|---|---|---|---|
| Biological Samples | Serum, plasma, urine, tissue extracts | 0.5-2 mL (liquid) 50-100 mg (tissue) | Freeze at -20°C or -80°C for long-term storage |
| Food and Beverage | Liquid (juices, wines, etc.) or solid (fruits, candies) | 10-50 mL (liquid) 5-10 g (solid) | Refrigerate at 4°C |
| Pharmaceuticals | Powders, tablets, liquid formulations | 5-20 mg (active ingredient) | Room temperature or per product label instructions |
| Cosmetic and Personal Care | Creams, lotions, gels, serums | 2-5 g | Room temperature, away from heat and sunlight |
If you have specific sample types or conditions not listed above, our team at Creative Proteomics will work with you to accommodate your needs and ensure proper handling.
PCA chart
PLS-DA point cloud diagram
Plot of multiplicative change volcanoes
Metabolite variation box plot
Pearson correlation heat map
Metabolites and Genes behind Cardiac Metabolic Remodeling in Mice with Type 1 Diabetes Mellitus
Journal: International Journal of Molecular Sciences
Published: 2022
Background
Diabetic cardiomyopathy (DMCM) is a major complication in diabetes, with Type 1 diabetes mellitus (T1DM) significantly affecting cardiac metabolic processes. Despite the use of intensive glycemic control, there remains a limited understanding of how differential gene expression and metabolite changes contribute to metabolic remodeling in the T1DM heart. The Akita mouse model, which develops T1DM through a genetic mutation in the insulin gene, is used to study these processes without the off-target effects of chemically induced diabetes models. This study employs metabolomics (LC-MS) and genomics (next-generation sequencing) to identify disrupted metabolic pathways in the T1DM heart, aiming to better understand the metabolic derangements and provide a foundation for developing therapeutic strategies. Key pathways identified include ketogenesis, fatty acid beta-oxidation, and cholesterol biosynthesis.
Materials & Methods
Animals
We procured WT (C57BL/6J) and Ins2+/−Akita mice from The Jackson Laboratory and maintained them at the University of Nebraska Medical Center. The mice, aged 14–16 weeks, were provided standard chow and water ad libitum. All procedures adhered to NIH guidelines and received IACUC approval (protocol 19-054-06-FC).
Genotyping
Genotyping followed our published protocol, isolating DNA from ear tissue. PCR amplification used specific primers, and products underwent restriction digestion and gel electrophoresis to confirm genotypes.
Blood Glucose Measurement
Mice were fasted for 6–8 hours. Blood glucose was measured from tail samples using an Accu-Chek glucometer.
Serum Insulin Measurement
Serum insulin was measured via ELISA after collecting blood from the vena cava, following the manufacturer's protocol.
Overall Study Design for Metabolomics and Genomics Analyses
After validating T1DM phenotypes, LV heart tissue was used for metabolomic and genomic analyses. Previous studies indicated cardiac issues in Akita mice at this age. Sample sizes were n = 4 for metabolomics and n = 2 for genomics.
Liquid Chromatography-Mass Spectrometry (LC-MS) Sample Preparation
For metabolite evaluation, LV tissue was homogenized and prepared for LC-MS analysis.
LC-MS Metabolite Analysis
Non-sugar and sugar metabolites were analyzed using different methods on respective UPLC and LC systems, following
RNA Extraction
RNA was isolated using the mirVana kit, ensuring purity for downstream applications.
Next Generation RNA Sequencing
High-quality RNA underwent library preparation and sequencing, generating approximately 20 million reads per sample. Differential gene expression was analyzed using the Tuxedo pipeline.
Ingenuity Pathway Analysis
Metabolic pathways associated with differentially expressed genes and metabolites were analyzed using IPA software.
Statistical Methods
Data are expressed as mean ± SEM. Paired Student's t-tests were used for comparisons, and GraphPad Prism software facilitated statistical analyses.
Results
Validation of Akita Mice
Akita mice, which carry a mutation in the Ins2 gene leading to Type 1 Diabetes Mellitus (T1DM), were validated for the T1DM phenotype. Compared to wild-type (WT) mice, Akita mice showed significantly higher fasting blood glucose levels and lower serum insulin levels, confirming their diabetic condition.
Metabolomic Analyses
Metabolomic profiling of left ventricular (LV) tissue in Akita mice using LC-MS identified 108 disrupted metabolic pathways, including notable changes in the tricarboxylic acid (TCA) cycle. Key metabolites such as acetyl CoA, citric acid, oxaloacetic acid, and ADP were downregulated, while NADH, fumaric acid, malic acid, and ATP were upregulated. A heatmap visualized the altered metabolite levels in the TCA cycle between Akita and WT mice.
LC-MS metabolomics analysis of Akita compared to WT hearts. (Ai, Aii) The top predicted canonical metabolic pathways disrupted in the Akita heart, identified through metabolite IPA analysis, exhibited a –log(p-value) > 1.3. (B) A heatmap illustrates the percent change of individual metabolites associated with these pathways in the Akita and WT hearts, calculated from the expression log ratio; p-value < 0.05, n = 4.
Differential expression of key metabolites involved in the tricarboxylic acid (TCA) cycle in the Akita heart by Ingenuity Pathway Analyses (IPA) of metabolites. (A) TCA cycle metabolite intermediates in Akita versus WT mice. Line indicates no change between groups. *FADH levels were undetected. (B) Heatmap indicating percent change of single metabolite levels associated with the TCA cycle in Akita and WT mice. Analysis conducted with Ingenuity Pathway Analysis software. n = 4.
Genomic Analyses
Next-generation sequencing of LV tissue revealed 30 disrupted metabolic pathways in the Akita heart. Genes associated with these pathways were analyzed using Ingenuity Pathway Analysis (IPA), showing significant changes in gene expression linked to key metabolic processes. A heatmap depicted the differential expression of these genes.
Genes and Metabolites Associated with Disrupted Metabolic Pathways
Combined analysis of metabolomics and genomics data showed 15 common metabolic pathways disrupted in the Akita heart. These pathways, such as ketogenesis, beta-oxidation, and cholesterol biosynthesis, were identified through the overlap of 108 metabolomic and 30 genomic pathways.
Upstream Regulators of Genes
Further analysis identified key transcription factors serving as upstream regulators of the 15 disrupted metabolic pathways. These transcription factors play a role in mediating the changes observed in both the genomic and metabolomic datasets, offering insights into the regulatory mechanisms driving T1DM-induced cardiac metabolic remodeling.
Reference
- Kambis, Tyler N., Hamid R. Shahshahan, and Paras K. Mishra. "Metabolites and Genes behind Cardiac Metabolic Remodeling in Mice with Type 1 Diabetes Mellitus." International journal of molecular sciences 23.3 (2022): 1392.
How do you ensure the integrity of samples during storage and transport?
We provide specific guidelines for sample collection, storage, and transport to maintain sample integrity. Biological samples should be frozen at -20°C or -80°C for long-term storage, while food and beverage samples should be refrigerated at 4°C. We recommend using appropriate containers to prevent contamination and degradation. For transport, samples should be kept on dry ice or in insulated coolers to maintain low temperatures. Following these guidelines minimizes the risk of metabolite degradation, ensuring accurate analysis.
Can you explain how you differentiate between malic acid and its isomers during analysis?
Differentiating malic acid from its isomers is crucial for precise quantification and characterization. In our GC-MS analysis, we utilize specific temperature programs and solvent choices that favor the volatilization of malic acid and its isomers, allowing us to capture distinct mass-to-charge ratios during detection. Additionally, we implement retention time comparisons against known standards. The combination of retention time, mass spectral analysis, and calibration curves specific to each isomer ensures that we can accurately quantify malic acid and differentiate it from similar compounds.
How do you handle potential interferences from other metabolites in complex biological samples?
In complex biological samples, various metabolites can potentially interfere with the detection of malic acid. To mitigate this, we implement rigorous sample preparation protocols that include extraction steps optimized for removing interfering substances. For example, we may use solid-phase extraction (SPE) to isolate malic acid while reducing matrix effects. Furthermore, we incorporate internal standards during analysis to correct for variability and interference, ensuring that our quantification of malic acid remains accurate.
What is the detection limit for malic acid using your analytical methods?
The detection limit varies depending on the analytical technique used. For HPLC, we typically achieve detection limits in the low micromolar range. GC-MS can provide even lower detection limits, often in the nanomolar range, due to its high sensitivity. LC-MS systems, particularly the Thermo Scientific Q Exactive™ Orbitrap, can detect malic acid at trace levels, often below 1 nanomolar. These detection limits make our services suitable for a wide range of applications, from food quality assessment to clinical research.
Metabolites and Genes behind Cardiac Metabolic Remodeling in Mice with Type 1 Diabetes Mellitus
Kambis, Tyler N., Hamid R. Shahshahan, and Paras K. Mishra.
Journal: International Journal of Molecular Sciences
Year: 2022
DOI: https://doi.org/10.3390/ijms23031392
Plant Growth Promotion, Phytohormone Production and Genomics of the Rhizosphere-Associated Microalga, Micractinium rhizosphaerae sp. nov.
Quintas-Nunes, Francisco, et al.
Journal: Plants
Year: 2023
DOI: https://doi.org/10.3390/plants12030651
Thermotolerance capabilities, blood metabolomics, and mammary gland hemodynamics and transcriptomic profiles of slick-haired Holstein cattle during mid lactation in Puerto Rico
Contreras-Correa, Zully E., et al.
Journal: Journal of Dairy Science
Year: 2024
DOI: https://doi.org/10.3168/jds.2023-23878
