Reproducible profiling of the gut microbiota using surplus clinical Faecal Immunochemical Test (FIT) samples

This study demonstrates that surplus Faecal Immunochemical Test (FIT) samples remain stable for up to 14 days and yield bacterial 16S rRNA sequencing results comparable to standard whole-stool samples, validating their use for large-scale, low-cost gut microbiota research.

The Gist

The Big Idea: Turning "Trash" into Treasure

Imagine you go to the doctor and give a tiny sample of your poop to check for signs of colon cancer. This is a standard test called a qFIT (Quantitative Faecal Immunochemical Test).

Usually, the sample sits in a special liquid in a tube, gets checked for blood in the stool, and is then thrown away (unless retesting is necessary). It's like buying a giant pizza, taking one tiny slice to taste, and throwing the rest in the trash.

This study asked a simple question: Can we use that "thrown away" part of the sample to learn about the billions of tiny bacteria living in our guts?

The answer is a resounding YES.

The Problem: The "Tiny Scoop" Challenge

The specific test used in this study (the EXTEL HEMO-AUTO MC) is very efficient but collects a very small amount of poop (only 2 milligrams). That's like trying to describe a whole forest by looking at just two pine needles. Scientists were worried that:

1. There might not be enough "forest" (bacteria) to study.
2. The "pine needles" might change or rot while waiting to be tested (stability).
3. The tiny sample might not represent the whole forest accurately compared to a big bucket of poop.

The Experiment: The "Time-Travel" Test

To solve this, the researchers set up three different scenarios:

1. The "Volume" Test (Does size matter?)
They took frozen poop samples and put them into the tiny test tubes. They tried using different amounts of the liquid to see if they could get enough DNA (the bacteria's instruction manual).

• The Result: It didn't matter how much liquid they used. Even with the tiny amount, they got a clear picture of the bacteria. It's like realizing you can identify a whole song just by listening to a 5-second clip.

2. The "Fresh vs. Old" Test (Does time matter?)
They took fresh poop from 16 healthy volunteers. They put four tiny probes into each person's sample.

• Probe 1: Tested immediately (Day 0).
• Probe 2: Left out on the counter for 4 days (mimicking the time it takes to mail a sample).
• Probe 3 & 4: Left on the counter, then put in the fridge for a week or two (mimicking how labs store them).
• The Result: The bacteria looked almost exactly the same, whether tested immediately or two weeks later. The special liquid in the test tube acted like a preservative, keeping the bacteria "frozen in time" so they didn't rot or change.

3. The "Real World" Test (Does it work for regular people?)
They took 100 leftover test tubes from real patients who had been tested for rectal bleeding in a hospital. These weren't perfect lab samples; they were messy, real-world samples.

• The Result: 75% of these real-world samples had enough DNA to study. That's a huge success rate for samples collected by regular people at home.

The Conclusion: A New Superpower for Science

The study found that these "leftover" test tubes are almost identical to samples collected in big buckets. They are stable for at least two weeks, and they contain enough information to map out a person's gut microbiome.

Why is this a big deal?

• Waste Not, Want Not: Millions of these samples are thrown away every year. Now, instead of being discarded, they are available for reuse. While studying them still requires resources and funding, this approach unlocks a massive new source of data that was previously lost.
• Big Picture: Instead of studying 50 people, researchers can study 50,000 people. This allows them to find links between gut bacteria and diseases like diabetes, heart disease, and cancer with much higher accuracy.
• Long-Term Tracking: Since people get tested every two years, scientists can track how a person's gut bacteria changes as they age, without asking them to do anything extra.

The Takeaway Metaphor

Think of the gut microbiome as a giant, complex orchestra.

• Old way: Scientists had to ask the whole orchestra to come to the studio, set up expensive microphones, and record them. It was hard, expensive, and only a few orchestras could be recorded.
• New way: This study discovered that the "leftover" samples are like recording the orchestra from the back of the concert hall. It's not quite as loud as being on stage, but the music is clear enough to tell you exactly who is playing, what song they are playing, and how the music changes over time. And best of all, the concert is happening every day, and we have millions of recordings we didn't know we could use!

This research opens the door to a new era of large-scale health studies using samples that were previously destined for the trash can.

Technical Summary

1. Problem Statement

• Context: Quantitative Faecal Immunochemical Tests (qFIT), specifically the EXTEL HEMO-AUTO MC system, are widely used globally for colorectal cancer (CRC) screening and symptomatic testing. These tests detect faecal haemoglobin using a small probe that collects only 2 mg of faeces into a 2 ml buffer.
• The Gap: While millions of these samples are processed annually, the vast majority of the sample (the remaining buffer after the ~6 µl used for haemoglobin testing) is discarded.
• The Challenge: Previous studies on gut microbiota using FIT samples have focused on devices collecting larger amounts of faeces (e.g., 10 mg in OC-Sensor or FOB-Gold systems). It was unknown if the EXTEL HEMO-AUTO MC device, with its significantly smaller faecal input (2 mg) and specific proprietary buffer, could yield sufficient and stable DNA for 16S rRNA gene sequencing. Furthermore, the stability of these samples over the timeframes typical of clinical logistics (postage and laboratory storage) had not been validated.

2. Methodology

The study utilized three distinct sample sets to validate the feasibility, stability, and comparability of the EXTEL HEMO-AUTO MC qFIT for microbiome analysis:

• Sample Set 1 (Optimization): Two frozen stool samples from prostate cancer patients were used to optimize DNA extraction protocols. Researchers tested different volumes of the qFIT buffer/faeces suspension (450 µl vs. the full 2 ml) and compared them against whole stool samples (5 g) to determine if sample volume or freezing affected bacterial profiles.
• Sample Set 2 (Stability & Comparability): Sixteen healthy volunteers provided fresh stool samples.
  • Protocol: Four qFIT probes were inserted into each volunteer's stool.
  • Timepoints: Probes were processed at Day 0 (immediate), Day 4 (simulating room temperature postage), and Days 7 and 14 (simulating laboratory storage at 4°C).
  • Controls: These were compared against "whole stool" controls (5 g homogenized in PBS/glycerol) processed at Day 0 and Day 4.
  • Sequencing: 16S rRNA gene sequencing (V1-V2 region) was performed using Illumina MiSeq.
• Sample Set 3 (Real-world Feasibility): 100 anonymous surplus qFIT samples from symptomatic patients (collected in routine clinical practice) were analyzed solely for DNA yield to determine if they met the threshold for successful sequencing.
• Bioinformatics & Statistics:
  • Pipeline: Mothur (v1.48.0) for processing (quality filtering, alignment to SILVA, OTU clustering at 97%).
  • Statistical Tools: Metastats, LEfSe, DESeq2, MaAsLin2, and PERMANOVA were used to assess alpha/beta diversity, differential abundance, and longitudinal stability.

3. Key Contributions

• Validation of a New Device: This is the first study to characterize the gut microbiota potential of the EXTEL HEMO-AUTO MC system, which is distinct from previously studied FITs due to its smaller faecal collection volume (2 mg vs. 10 mg).
• Stability Data: The study provides empirical evidence that qFIT samples remain stable for 14 days under conditions mimicking clinical logistics (4 days at room temperature followed by 10 days at 4°C).
• Resource Repurposing: It demonstrates a pathway to repurpose "waste" clinical samples for large-scale, low-cost population microbiome studies without requiring new sample collection protocols.

4. Key Results

• DNA Yield & Sufficiency:
  • In the real-world cohort (Sample Set 3), 75% of symptomatic patient qFITs yielded sufficient DNA (>0.432 ng/µl) for 16S sequencing.
  • The entire 2 ml buffer volume did not significantly alter results compared to smaller aliquots, allowing for flexibility in extraction protocols.
• Stability Over Time:
  • Bacterial composition and diversity in qFIT samples remained stable over 14 days.
  • No statistically significant differences were found in alpha diversity (Shannon, Simpson) or beta diversity between Day 0, 4, 7, and 14 timepoints.
  • Longitudinal analysis (MaAsLin2) showed no significant associations between bacterial taxa and time.
• Comparability with Whole Stool:
  • Diversity: Whole stool samples showed slightly higher Observed Richness (likely due to the larger input mass of 5g vs. 2mg), but evenness (Shannon/Simpson indices) was comparable.
  • Composition: Beta diversity analysis (PCoA, PERMANOVA) showed that samples clustered primarily by donor, not by sampling method (qFIT vs. whole stool) or timepoint.
  • Taxonomy: No significant differences in bacterial proportional abundance were found at the family, genus, or OTU levels between qFIT and whole stool samples after multiple testing corrections. One genus (Paraprevotella) showed a minor difference in one analysis, but this was not replicated by other statistical methods and had negligible effect size.
• Technical Robustness: The results were consistent across different statistical frameworks (Metastats, LEfSe, DESeq2), confirming the reliability of the qFIT-derived microbiome data.

5. Significance and Implications

• Large-Scale Epidemiology: This approach unlocks the potential for longitudinal, population-based microbiome studies involving tens of thousands of individuals (e.g., ages 50–74 in screening programs) at a fraction of the cost of fresh stool collection.
• Clinical Integration: It allows for the integration of microbiome data with existing "big data" health records (e.g., linking microbiota to CRC outcomes, cardiovascular disease, diabetes, and inflammatory conditions) without disrupting current clinical workflows.
• Future Applications:
  • CRC Research: Enables the study of microbiome changes during cancer development and treatment response using routine screening samples.
  • Diagnostic Development: Could lead to the identification of specific microbial panels for CRC detection, potentially reducing the need for invasive colonoscopies in low-risk patients.
  • Methodological Shift: While 16S rRNA sequencing is feasible, the study notes that shotgun metagenomics may be limited for these samples due to lower DNA yields in some real-world cases, suggesting 16S remains the primary practical tool for this specific sample type.

In conclusion, the paper establishes that surplus EXTEL HEMO-AUTO MC qFIT samples are a reliable, stable, and cost-effective resource for gut microbiota research, bridging the gap between routine clinical screening and advanced microbiome science.