Microbiome Sample Preparation Technology Market Size, Share & Trends Analysis Report By Product (Instruments, Consumables), By Workflow, By Application, By Disease, By End Use, By Region, And Segment Forecasts, 2025 - 2030

Microbiome Sample Preparation Technology Market Size, Share & Trends Analysis Report By Product (Instruments, Consumables), By Workflow, By Application, By Disease, By End Use, By Region, And Segment Forecasts, 2025 - 2030


Microbiome Sample Preparation Technology Market Growth & Trends

The global microbiome sample preparation technology market size is expected to reach USD 368.74 million in 2030 and is expected to expand at a CAGR of 6.09% from 2025 to 2030. The rising importance of the microbiome as an area of study for Inflammatory Bowel Disease (IBD) research along with the innovation in genome sequencing techniques are significant contributors to the market growth. Crohn's disease is one of the most common diseases of IBD and surging incidence rates in North America and Western Europe, with approximately 100 to 300 per 100,000 people being affected in both regions, are likely to accelerate the R&D for the same.

A metabolite-based treatment method is highly promising for Dysbiosis, despite its existing limitations. Within coming years, researchers are anticipated to require to incorporate metabolomics characterization of the microbial ecosystem into their standard toolkit, enabling the community to define functional signatures for disease states that have previously only been linked to compositional and metagenomic changes.

Additionally, the development of novel metabolite sensors will eventually allow for the targeted regulation of downstream signaling cascades in circumstances when the host's reaction to the microbiome is excessive. Metabolite-based treatments provide a direct and actionable way to combat the host effects of dysbiosis. The era of metabolite research in microbiome science has already begun, and sustained efforts could lead to the discovery of clinically applicable therapeutics for dysbiosis-related disorders.

Other factors such as the rising penetration of personalized medicine are likely to impact the usage of microbiome sample preparation technology. Various research institutes are conducting studies to understand the gut microbiome and its impact on diet followed by the identification of effective therapeutics. For instance, a study was carried out in 2019 at the Weizmann Institute of Science to develop an algorithm based on machine learning and study glycemic response after consuming similar food. The study concluded that patients displayed different glycemic responses, even when food consumed is the same as microbiome played an important determinant of the blood sugar levels than genetic data.

The COVID-19 pandemic accelerated the use of microbiome sample preparation technology for the research proposed. There have been various studies in progress focusing on the alteration of gut microbiome post-COVID-19 infection. According to studies, the abundance of phyla Firmicutes, Bacteroidetes, and Proteobacteria were observed within patients diagnosed with the virus. Furthermore, fecal metabolomic studies in COVID-19 patients have revealed probable amino acid-related pathways that link gut microbiota to inflammation.

However, the high cost of instruments in this market is anticipated to have adverse effects on the growth rate. Emerging nations with low spending capability on healthcare and sanitation are observed to have a high risk of gastrointestinal disorders. With the potential high risk of infection in the population, low penetration of technology within these regions is likely to act as a market restraint within specific countries.

Microbiome Sample Preparation Technology Market Report Highlights
  • By product, the consumables segment is anticipated to exhibit a high growth rate in the forecast period. This is attributed to the increasing demand for library quantitation and amplification kits for specialized enzymes and reagents that provide efficient processing and low amplification bias
  • By workflow, the sample extraction/Isolation segment is estimated to dominate the microbiome sample preparation technology market with a share of 24.08% in 2024. Studying human gut microbial in disease depends on the accuracy of microbial data acquisition through the extraction process
  • By application, the DNA sequencing segment is estimated to dominate the microbiome sample preparation technology market with a share of 25.64% in 2024. This is attributed to the increasing use of amplicon-based next-generation sequencing for marker genes, an important application in rapid pathogen identification
  • By disease type, the gastrointestinal disorders segment dominated the market in 2024, with a share of 53.96%. . Microbiome analysis allows clinicians to identify specific unknown pathogens and track the microbiota and microbiome in regards to illness status and treatment
  • By end-use, diagnostic labs segment dominated the market in 2024, with a share of 62.01% due to the launch of various projects and consistent research activities and clinical trials to understand the role of the gut microbiome in the diagnosis of various chronic diseases
  • North America dominated the market in 2024 owing to a great performance by key players and rising demand for consumables for downstream applications
  • The Asia Pacific is predicted to grow at a significant rate throughout the forecast period due to continuous efforts by major companies to capitalize on opportunities and expand their presence in Asian markets
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Chapter 1. Methodology and Scope
1.1. Market Segmentation and Scope
1.2. Research Methodology
1.2.1. Information Procurement
1.3. Information or Data Analysis
1.4. Methodology
1.5. Research Scope and Assumptions
1.6. Market Formulation & Validation
1.7. Country Based Segment Share Calculation
1.8. List of Data Sources
Chapter 2. Executive Summary
2.1. Market Outlook
2.2. Segment Outlook
2.3. Competitive Insights
Chapter 3. Virtual Cards Market Variables, Trends, & Scope
3.1. Market Lineage Outlook
3.2. Market Dynamics
3.2.1. Market Driver Analysis
3.2.2. Market Restraint Analysis
3.2.3. Industry Challenge
3.3. Virtual Cards Market Analysis Tools
3.3.1. Industry Analysis - Porter’s
3.3.1.1. Bargaining power of the suppliers
3.3.1.2. Bargaining power of the buyers
3.3.1.3. Threats of substitution
3.3.1.4. Threats from new entrants
3.3.1.5. Competitive rivalry
3.3.2. PESTEL Analysis
3.3.2.1. Political landscape
3.3.2.2. Economic landscape
3.3.2.3. Social landscape
3.3.2.4. Technological landscape
3.3.2.5. Environmental landscape
3.3.2.6. Legal landscape
Chapter 4. Virtual Cards Market: Card Type Estimates & Trend Analysis
4.1. Segment Dashboard
4.2. Virtual Cards Market: Card Type Movement Analysis, 2024 & 2030 (USD Million)
4.3. Credit Card
4.3.1. Credit Card Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
4.4. Debit Card
4.4.1. Debit Card Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
Chapter 5. Virtual Cards Market: Product Type Estimates & Trend Analysis
5.1. Segment Dashboard
5.2. Virtual Cards Market: Product Type Movement Analysis, 2024 & 2030 (USD Million)
5.3. B2B Virtual Cards
5.3.1. B2B Virtual Cards Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
5.4. B2C Remote Payment Virtual Cards
5.4.1. B2C Remote Payment Virtual Cards Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
5.5. C2B POS Virtual Cards
5.5.1. C2B POS Virtual Cards Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
Chapter 6. Virtual Cards Market: Application Estimates & Trend Analysis
6.1. Segment Dashboard
6.2. Virtual Cards Market: Application Movement Analysis, 2024 & 2030 (USD Million)
6.3. Business Use
6.3.1. Business Use Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
6.4. Consumer Use
6.4.1. Consumer Use Cards Market Revenue Estimates and Forecasts, 2017 - 2030 (USD Million)
Chapter 7. Virtual Cards Market: Regional Estimates & Trend Analysis
7.1. Virtual Cards Market Share, By Region, 2024 & 2030 (USD Million)
7.2. North America
7.2.1. North America Virtual Cards Market Estimates and Forecasts, 2017 - 2030 (USD Million)
7.2.2. U.S.
7.2.2.1. U.S. Virtual Cards Market Estimates and Forecasts, 2017 - 2030 (USD Million)
7.2.3. Canada
7.2.3.1. Canada Virtual Cards Market Estimates and Forecasts, 2017 - 2030 (USD Million)
7.2.4. Mexico
7.2.4.1. Mexico Virtual Cards Market Estimates and Forecasts, 2017 - 2030 (USD Million)
7.3. Europe
7.3.1. Europe Virtual Cards Market Estimates and Forecasts, 2017 - 2030 (USD Million)
7.3.2. UK
7.3.2.1. UK Virtual Cards Market Estimates and Forecasts, 2017 - 2030 (USD Million)
7.3.3. Germany
7.3.3.1. Germany Virtual Cards Market Estimates and Forecasts, 2017 - 2030 (USD Million)
7.3.4. France
7.3.4.1. France Virtual Cards Market Estimates and Forecasts, 2017 - 2030 (USD Million)
7.4. Asia Pacific
7.4.1. Asia Pacific Virtual Cards Market Estimates and Forecasts, 2017 - 2030 (USD Million)
7.4.2. China
7.4.2.1. China Virtual Cards Market Estimates and Forecasts, 2017 - 2030 (USD Million)
7.4.3. Japan
7.4.3.1. Japan Virtual Cards Market Estimates and Forecasts, 2017 - 2030 (USD Million)
7.4.4. India
7.4.4.1. India Virtual Cards Market Estimates and Forecasts, 2017 - 2030 (USD Million)
7.4.5. South Korea
7.4.5.1. South Korea Virtual Cards Market Estimates and Forecasts, 2017 - 2030 (USD Million)
7.4.6. Australia
7.4.6.1. Australia Virtual Cards Market Estimates and Forecasts, 2017 - 2030 (USD Million)
7.5. Latin America
7.5.1. Latin America Virtual Cards Market Estimates and Forecasts, 2017 - 2030 (USD Million)
7.5.2. Brazil
7.5.2.1. Brazil Virtual Cards Market Estimates and Forecasts, 2017 - 2030 (USD Million)
7.6. Middle East and Africa
7.6.1. Middle East and Africa Virtual Cards Market Estimates and Forecasts, 2017 - 2030 (USD Million)
7.6.2. UAE
7.6.2.1. UAE Virtual Cards Market Estimates and Forecasts, 2017 - 2030 (USD Million)
7.6.3. KSA
7.6.3.1. KSA Virtual Cards Market Estimates and Forecasts, 2017 - 2030 (USD Million)
7.6.4. South Africa
7.6.4.1. South Africa Virtual Cards Market Estimates and Forecasts, 2017 - 2030 (USD Million)
Chapter 8. Competitive Landscape
8.1. Company Categorization
8.2. Company Market Positioning
8.3. Company Heat Map Analysis
8.4. Company Profiles/Listing
8.4.1. American Express Company
8.4.1.1. Participant’s Overview
8.4.1.2. Financial Performance
8.4.1.3. Product Benchmarking
8.4.1.4. Strategic Initiatives
8.4.2. BTRS Holdings, Inc.
8.4.2.1. Participant’s Overview
8.4.2.2. Financial Performance
8.4.2.3. Product Benchmarking
8.4.2.4. Strategic Initiatives
8.4.3. Wise Payments Limited
8.4.3.1. Participant’s Overview
8.4.3.2. Financial Performance
8.4.3.3. Product Benchmarking
8.4.3.4. Strategic Initiatives
8.4.4. JPMorgan Chase & Co.
8.4.4.1. Participant’s Overview
8.4.4.2. Financial Performance
8.4.4.3. Product Benchmarking
8.4.4.4. Strategic Initiatives
8.4.5. Marqeta, Inc.
8.4.5.1. Participant’s Overview
8.4.5.2. Financial Performance
8.4.5.3. Product Benchmarking
8.4.5.4. Strategic Initiatives
8.4.6. MasterCard
8.4.6.1. Participant’s Overview
8.4.6.2. Financial Performance
8.4.6.3. Product Benchmarking
8.4.6.4. Strategic Initiatives
8.4.7. Skrill USA, Inc.
8.4.7.1. Participant’s Overview
8.4.7.2. Financial Performance
8.4.7.3. Product Benchmarking
8.4.7.4. Strategic Initiatives
8.4.8. Stripe, Inc.
8.4.8.1. Participant’s Overview
8.4.8.2. Financial Performance
8.4.8.3. Product Benchmarking
8.4.8.4. Strategic Initiatives
8.4.9. WEX, Inc.
8.4.9.1. Participant’s Overview
8.4.9.2. Financial Performance
8.4.9.3. Product Benchmarking
8.4.9.4. Strategic Initiatives
8.4.10. Adyen
8.4.10.1. Participant’s Overview
8.4.10.2. Financial Performance
8.4.10.3. Product Benchmarking
8.4.10.4. Strategic Initiatives

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