What are the hold times?

The hold times for each analysis are listed below:


PLFA24-48 hours
CENSUS24-48 hours
CENSUS-Expression (RNA)24 hours
Heterotrophic Plate Counts24-48 hours
ORm7-10 days
Acidity Testing7-10 days
NGS24-48 hours
Most Probable Numbers (MPNs)24-48 hours

What do the PLFA structural groups represent?

The PLFA in a sample can be separated into particular types, and the resulting PLFA “profile” reflects the proportions of the categories of organisms present in the sample. Because groups of bacteria differ in their metabolic capabilities, determining which bacterial groups are present and their relative distributions within the community can provide information on what metabolic processes are occurring at that location. This in turn can also provide information on the subsurface conditions (i.e. oxidation/reduction status, etc.).  The following table describes the six major structural groups used and their potential relevance to site specific projects.


PLFA Structural Group

General classification

Potential Relevance to Bioremediation Studies

Monoenoic (Monos)

Abundant in Proteobacteria (Gram negative bacteria), typically fast growing, utilize many carbon sources, and adapt quickly to a variety of environments.

Proteobacteria is one of the largest groups of bacteria and represents a wide variety of both aerobes and anaerobes.  The majority of Hydrocarbon utilizing bacteria fall within the Proteobacteria

Terminally Branched Saturated (TerBrSats)

Characteristic of Firmicutes (Low G+C Gram-positive bacteria), and also found in Bacteriodes, and some Gram-negative bacteria (especially anaerobes).

Firmicutes are  indicative of presence of  anaerobic fermenting bacteria (mainly Clostridia/Bacteriodes-like), which produce the H2 necessary for reductive dechlorination.

Branched Monoenoic  (BrMonos)

Found in the cell membranes of micro-aerophiles and anaerobes, such as sulfate- or iron-reducing bacteria

In contaminated environments high proportions are often associated with anaerobic sulfate and iron reducing bacteria.

Mid-Chain Branched Saturated (MidBrSats)

Common in sulfate reducing bacteria and also Actinobacteria (High G+C Gram-positive bacteria).

In contaminated environments high proportions are often associated with anaerobic sulfate and iron reducing bacteria.

Normal Saturated  (Nsats)

Found in all organisms.

High proportions often indicate less diverse populations.


Found in eukaryotes such as fungi, protozoa, algae, higher plants, and animals.

Eukaryotic scavengers will often prey on contaminant utilizing bacteria.

What does slowed growth or decreased permeability mean?

Ratios for slowed growth and for decreased permeability of the cell membrane provide information on the “health” of the Gram negative community, that is, how this population is responding to the conditions present in the environment. It should be noted that one must be cautious when interpreting these measures from only one sampling event.  The most effective way to use the physiological status indicators is in long term monitoring and comparing how these ratios increase/decrease over time.

A marked increase in either of these ratios suggests a change in environment which is less favorable to the Gram negative Proteobacteria population. The ratio for slowed growth is a relative measure, and does not directly correspond to log or stationary phases of growth, but is useful as a comparison of growth rates among sampling locations and also over time. An increase in this ratio (i.e. slower growth rate) suggests a change in conditions which is not as supportive of rapid, “healthy” growth of the Gram negative population, often due to reduced available substrate (food).  A larger ratio for decreased permeability suggests that the environment has become more toxic to the Gram negative population, requiring energy expenditure to produce trans fatty acids in order to make the membrane more rigid.

What does the concentration of biomass mean?

The overall abundance of microbes within a given sample is often used as an indicator of the potential for bioremediation to occur. The following are benchmarks that can be used to understand whether the biomass levels are low, moderate or high.

Low: 10e3 to 10e4 cells/mL

Moderate: 10e5 to 10e6 cells/mL

High: 10e7 to 10e8 cells/mL

What is the detection limit for PLFA analysis?

The limit of detection for PLFA analysis is ~50 picomoles of total PLFA and the limit of quantitation is ~150 picomoles of total PLFA (or ~10e3 cells/mL).  Samples which contain PLFA amounts at or below 50 pmol cannot be used to determine biomass, likewise samples with PLFA content below ~150 pmol are generally considered to contain too few fatty acids to produce meaningful community composition data.

What is the difference between PLFA, NGS, and CENSUS?

MI offers three categories of cultivation independent analyses to characterize microbial communities: PLFA, NGS, and CENSUS.  Although the target biomarker molecules (phospholipids vs. DNA) and procedures (GC/MS vs. PCR) are extremely different, the overlying difference in the results provided by each technique is in the degree of resolution or specificity.  Choosing between these approaches, therefore, depends primarily upon the specificity of questions that need to be addressed and the current state of knowledge regarding the microbial process in question.

Phospholipid fatty acid (PLFA) analysis provides a robust measure of total biomass and a broad-based profile of the microbial community composition grouped into general categories such as anaerobic Gram negative bacteria, eukaryotes, and Proteobacteria.  Other than for stable isotope probing (SIP) studies, PLFA analysis is best suited for addressing more general questions such as whether a treatment increased (or decreased) total biomass or substantially changed redox conditions.

CENSUS results, on the other hand, are very specific – quantification of specific organisms (e.g. Dehalococcoides) and genes encoding specific functions (e.g. vinyl chloride reductases).  Thus, CENSUS analysis is most appropriate for answering targeted questions relating to reasonably well characterized microbial processes.  For example, CENSUS assays have been developed to quantify specific bacteria and functional genes responsible for biodegradation of a wide variety of common groundwater contaminants.

NGS provides a DNA based profile of the microbial community and allows identification of the predominant organisms generally to the family or genus level but cannot quantify specific organisms or microbial functions.  Sequence analysis is somewhat exploratory, seeking to answer the question “Who is there?”.  Most often, NGS analysis is performed when identification of the predominant organisms is required but little is known about the microbial community of the sample prior to analysis.

What is the turn around time for analysis?

The turn around time for each analysis is listed below.


PLFA (groundwater, Bio-Trap)21-30 days
PLFA (soil)30-45 days
CENSUS7-10 days
CENSUS-Expression (RNA)10-14 days
Heterotrophic Plate Counts10-14 days
Most Probable Numbers (MPNs)30-40 days
Oil Retention (ORm)14-20 days
Acidity Testing14-20 days
DGGE21-30 days

What levels of reports are available from MI?

Microbial Insights has a variety of reporting levels available for each analysis. For information on additional levels of QAQC reports, please contact us.  There are also report styles available for help with data assessment.

Can Microbial Insights receive international samples?

Yes.  Microbial Insights has an international soil permit and has received samples without problem from many different countries. Please see international shipment for additional information

Can Microbial Insights receive samples on Saturday?

Microbial Insights is now open on Saturdays.  However, coolers should be shipped to a FedEx drop location and held where an MI representative will collect them.  It is important to ship to the Saturday delivery address and follow all procedures as indicated under the sample shipment section.  Please note that due to the short hold time associated with RNA and culture, it is recommended that these samples NOT be shipped for Saturday delivery.

Do I need to add a preservative to my samples?

For most analyses, the only preservative that is required is that the samples are shipped on ice at 4c for next day delivery.

Samples collected for CENSUS-expression (RNA) must be collected using the bio-flo sampling approach or bio-trap samplers. Following collection, each bio-flo sample MUST BE preserved using a special RNA preservative which is shipped along with your other sampling supplies. Please see the bio-flo sampling protocol for more information about this approach.

How can community composition data be used to help manage my site?

It is important to understand that microbial communities are a mixture of different types of bacteria (e.g. aerobes, sulfate reducers, methanogens, etc) with the abundance of each group behaving like a seesaw, i.e. as the population of one group increases, another is likely decreasing, mostly due to competition for available resources.  The PLFA profile of a sample provides a “fingerprint” of the microbial community, showing relative proportions of the specific bacterial types at the time of sampling. This is a great tool for detecting shifts within the community over time and also to evaluate similarities/differences between sampling locations. It is important to note that PLFA analysis of community composition analyzes the microbes directly, not just secondary breakdown products. So this provides direct evidence of how the entire microbial community is responding to the treatment.

How do I know if a change in biomass is significant?

One of the primary functions of using PLFA analysis at contaminated sites is to evaluate how a community responds following a given treatment. How does one know if the changes observed between two events are significant?  As a general rule, biomass levels which increase or decrease by at least an order of magnitude are considered to be significant.  However, changes in biomass levels of less than an order of magnitude may still show a trend.  It is important to remember that many factors can affect microbial growth, so factors other than the treatment could be influencing the changes observed between sampling events.  Some of the factors to consider are:  temperature, moisture, pH, etc. The following illustration depicts three types of changes that occurred over time and the conclusions that could be drawn.


Conclusions from above graph:

  • MW-1 showed a trend of biomass levels increasing steadily over time, although cell concentrations were ~10e4 cells/mL at each event.
  • MW-2 showed no notable trends or significant changes in biomass concentrations.
  • MW-3 showed a significant increase in biomass levels between the initial and 1st qtr sampling events (from ~10e5 to ~10e6 cells/mL)

How is biomass calculated?

Biomass levels are reported as cells per gram, mL or bead, and are calculated using a conversion factor of 20,000 cells/pmole of PLFA.  This conversation factor is an average based upon cells grown in a laboratory, and varies with the type of organism and environmental conditions.

How is biomass measured?

Viable biomass is determined from the total amount of PLFA detected in a given sample and is measured by GC-FID. Since phospholipids are an essential part of intact cell membranes they provide an accurate measure of viable cells.

How is the community composition data presented?

Community composition data is presented as a percentage (%) of the total amount of PLFA and results are illustrated as a stacked bar chart (see example below).

Should a monitoring well be purged prior to Bio-Trap deployment?

If the monitoring well has not been purged recently, it may be necessary prior to deployment.  MI recommends that three well volumes be removed to ensure contact with formation water and reduce well bore effects.

Should a well be purged prior to sample collection?

MI recommends that the same procedure be used for the microbial sampling as for the geochemical parameters.  As these results are often compared, it is important that samples be collected under similar monitoring well conditions.