This work was funded by the Academy of Finland (grant no. 311077 to Marjo Helander).

Conflicts of interest: none.

This protocol provides general guidance on how to quantify the effect of GBP on microbiomes based on the analysis of the EPSPS protein. The protocol has three major critical steps: (i) Quantification of the EPSPS protein from microbiome data. This step is critical because EPSPS is the direct target enzyme of the herbicide. Thus, species that have a copy of the EPSPS gene may be impacted by the use of GBP. Nevertheless, even species that lack a copy of the EPSPS gene may be impacted by the herbicide through alternative non-target mechanisms43,44. (ii) If the analysis of the EPSPS gene&#160;is not included in the design of the study, it is possible to get a good estimate by analyzing the 16S rRNA (bacteria) or ITS (fungi). In this case, it is essential to rely on a comprehensive reference table (e.g., the ATGC database provides sequences of the EPSPS protein from several closely related species). (iii) The EPSPS protein is divided into potentially sensitive or resistant to glyphosate depending on certain amino acid residues of the active site of the EPSPS. However, mutations affecting a single amino acid may alter this classification45 and transitions among classes may occur in a relatively short period of time14.
The potential sensitivity of organisms to glyphosate can be determined by reference genomes, amino acid markers and sequence alignments. (i) Reference genomes: The EPSPS enzyme can be classified as potentially sensitive (class I [alpha or beta]46,47) or resistant (classes II48,49, III50 and IV51) to glyphosate based on the presence of amino acid markers and motifs (in the case of class III). These amino acid markers and motifs are based on the location of amino acid residues in the EPSPS protein of Vibrio cholerae (vcEPSPS, class I), Coxiella burnetii (cbEPSPS, class II), Brevundimonas vesicularis (bvEPSPS, class III), and Streptomyces davawensis (sdEPSPS, class IV). (ii) Amino acid markers: Glyphosate interacts with the EPSPS enzyme and competes with phosphoenolpyruvate (PEP, the second substrate of the EPSPS enzyme)52,53. In certain species, small amino acid changes in the EPSPS sequence provide a higher affinity for the PEP and a resistance to glyphosate12, 14, 52, 54, 55. In other sequences, glyphosate binds the EPSPS sequence in a non-inhibitory conformation 45. Although many resistant 12,14,48,49,52,54,55 and tolerant56,57 EPSP sequences to glyphosate have been described, the current classification system for the EPSPS is divided into four major classes (I-IV )12 (Table 5). (iii) Sequence alignments: In order to classify an EPSPS enzyme, we performed pairwise alignments, with a multiple sequence alignment program-default parameters35-, of the query sequence against each one of the reference sequences (vcEPSPS, cbEPSPS, bvEPSPS and sdEPSPS). These alignments are necessary to identify the positions of the amino acid markers in the query sequence. As a result, an enzyme is classified as described12-class I, II and/or IV based on the presence of amino acid markers and class III based motif markers.
The protocol is based on four known types of EPSPS: one type is sensitive, the other three are resistant). However, approximately 10% of EPSPS sequences in prokaryotes are yet unclassified (16% in archaea and 8% in bacteria)12. Thus, further research should analyze those sequences to determine glyphosate sensitivity. The EPSPSClass server provides an option to test new genetic markers. The identification of known classes of the EPSPS is straightforward, as shown in section 4.4. and Figure 5. Furthermore, in those cases where users want to compare their own query and reference proteins, the server provides an option to manually include a reference sequence and a set of amino acid markers (Figure 11). This option can be utilized to identify novel classes of the EPSPS, as well as to test other herbicides and target sequences.
The analysis of the EPSPS class is determined by sequence analysis and the presence/absence of amino acid markers. This is a preliminary estimate that can be used for hypothesis testing in the field. Amino acid markers have been determined in the literature based on empirical and observational studies46,47,48,49,50,51. However, reference protein sequences to determine EPSPS class have been tested only in a limited number of species and may occasionally fail to explain resistance to glyphosate. The effect of compensatory mutations, and EPSPS-associated domains (mostly in fungi) may also affect the sensitivity to glyphosate58. This paper&#39;s analysis is based on four EPSPS classes. A survey of bacteria in the human gut microbiome showed that around 30% of them were unclassified (i.e., EPSPS proteins from these species do not belong to any of the known classes), and additional studies are needed to identify other EPSPS classes. Also, it should be noticed that the EPSPS protein sequence in bacteria and plants is unidomain, whereas fungal EPSPS proteins contain several domains59. Thus, a protein folding in fungi may lead to a different response of the EPSPS enzyme to glyphosate. Moreover, additional non-target mechanisms of resistance (e.g., efflux pumps and overexpression of the EPSPS gene13) or sensitivity to glyphosate (e.g., the effect of glyphosate on the mitochondrial transport chain12) are not considered.
Although GBPs have been around as a herbicide since 1974 and have been widely utilized since 1991, this is the first bioinformatics method to determine the potential sensitivity of organisms to glyphosate. The method is based on the identification of known amino acid residues in the target sequence. Thus, our method provides a baseline estimate of the potential effect of glyphosate on the species. In the near future, novel bioinformatics methods should include additional classes of the EPSPS protein to determine the potential sensitivity to glyphosate of unclassified sequences12,54,55. In addition, given that the exact behavior of the EPSPS enzyme may vary by single amino acid changes12,14,52,54,55, further in silico experiments should take into account small variations in the folding of the EPSPS protein, as well as the effect of the EPSPS-associated domains on the protein structure in fungi58. Moreover, it has been shown that tolerance to glyphosate may be produced by overexpression of the EPSPS protein56,57; thus bioinformatics analyses based on the amelioration of the codon usage60 may be utilized to identify novel EPSPS sequences that maximize or minimize gene expression.
Farmers, politicians, and decision-makers urgently need a thorough understanding of the risks associated with the heavy use of pesticides. Thus, both bioinformatic tools revealing the potential sensitivity of organisms to pesticides and well-replicated, randomized, and field-realistic experimental studies conducted in different environments are necessary. The presented bioinformatic method designed to examine organisms&#39; sensitivity to glyphosate can be modulated for other pesticides. Similarly, the methods of experimental ecology can be applied to study any related ecological questions. Together, the methods can be used to demonstrate casualties between field observations, genomic data, and pesticide use. All presented methods are invaluable in risk assessment. Bioinformatic methods can be used, for example, in monitoring microbial adaptations to agrochemicals and to provide a quantitative method to test the potential other associated risks, such as an increase in resistance of pathogens to agrochemicals, negative effects on microbes used as biological control agents in integrated pest management (IPM), and antibiotic resistance in bacteria.

The heavy use of pesticides in modern agriculture is clearly a major contributor to the decline of biodiversity1. This paper focuses on glyphosate because glyphosate-based products (GBPs) have become the most widely used pesticides globally due to their efficiency and affordable price2,3. In addition to killing weeds in agricultural fields, GBPs are commonly used in silviculture, urban environments, and home gardens; additionally, they have been proclaimed as nontoxic to non-target organisms if used in accordance with the manufacturer&#39;s instructions. However, an increasing number of recent studies have revealed that residues of glyphosate and its degradation products may be retained and transported in soils, thereby having cascading effects on non-target organisms4,5,6,7,8 . The effects of glyphosate are not limited only to plants-the shikimate pathway is present in many fungi and prokaryotes as well. Glyphosate targets the enzyme 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) in the shikimate pathway, also known as aroA9. This enzyme is at the center of the shikimate pathway in the synthesis of the three essential aromatic amino acids (phenylalanine, tyrosine, and tryptophan), and it is present in most prokaryotes, plants, and fungi10,11. Some microbial species have developed partial or absolute resistance to glyphosate by means of several mechanisms, including mutations in the EPSPS sequences. Thus, it has been suggested that the use of GBPs may have a direct effect on plant and animal microbiomes, including the human gut microbiome12,13,14. Nevertheless, the use of GBP may have an adverse impact on virtually any ecosystem function and service relying on microbes and microbe-facilitated processes. The consequent threats may concern biochemical soil processes, pollination biology, and animal and human wellbeing. This calls for a more comprehensive understanding of how glyphosate affects shikimate pathways and methods to assess the sensitivity of microbes to glyphosate.
In this protocol, we present a pipeline to test the effect of glyphosate and GBP on the microbiome, from field experiments to bioinformatics analyses. We describe in detail a recently published bioinformatics method that can be used to determine the potential sensitivity of organisms to glyphosate12. To the researchers&#39; knowledge, this is the first and so far, the only bioinformatics tool to assess the intrinsic sensitivity of the enzyme EPSPS to the active component of GBPs. This bioinformatics method is based on the detection of known amino acid markers in the glyphosate target enzyme (EPSPS)12. The pipeline is divided into five main working phases (Figure 1): 1) a brief introduction to two field experiments to test the effect of GBPs, 2) a brief summary of microbiome analyses (16S rRNA, ITS, and EPSPS gene), 3) gathering EPSPS sequences from public repositories, 4) determining the potential sensitivity of organisms to glyphosate, and 5) assessing the EPSPS class from universal microbial markers (16S rRNA and ITS).

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr >
			<td >2100 Bioanalyzer Instrument</td>
			<td >INVITEK Molecular</td>
			<td >1037100300</td>
			<td >Genomic DNA extraction from plant tissues</td>
		</tr>
		<tr >
			<td >dNTP mix (10 mM each)</td>
			<td >BIO-RAD</td>
			<td >1852196</td>
			<td>For PCR reactions</td>
		</tr>
		<tr >
			<td >GoTaq G2 DNA Polymerase kit</td>
			<td >Promega</td>
			<td >M7848</td>
			<td>PCR buffer and DNA Polymerase for PCR amplification</td>
		</tr>
		<tr >
			<td >Invisorb Spin Plant Mini Kit</td>
			<td >Agilent</td>
			<td>G2939B</td>
			<td>To check the concentration and quality of PCR products</td>
		</tr>
		<tr >
			<td >Ion Chip Minifuge</td>
			<td >sage science</td>
			<td >PIP0001</td>
			<td>For size fractionation of PCR amplicons</td>
		</tr>
		<tr >
			<td >Ion PGM System</td>
			<td >ThermoFisher Scientific</td>
			<td >4462921</td>
			<td>For targeted sequencing of microbial PCR products</td>
		</tr>
		<tr >
			<td >Ion PGM Torrent Server</td>
			<td >ThermoFisher Scientific</td>
			<td >4483643</td>
			<td>For targeted sequencing of microbial PCR products</td>
		</tr>
		<tr >
			<td >Pippinprep</td>
			<td >ThermoFisher Scientific</td>
			<td >4479672</td>
			<td>For targeted sequencing of microbial PCR products</td>
		</tr>
		<tr >
			<td >Pressure tank</td>
			<td >Berthoud</td>
			<td >102140</td>
			<td>For sprayin glyphosate based products in field</td>
		</tr>
		<tr >
			<td >Primers</td>
			<td >ThermoFisher Scientific</td>
			<td >R0192</td>
			<td>For PCR amplification</td>
		</tr>
		<tr >
			<td >Rotary tiller</td>
			<td >Grillo</td>
			<td>984511</td>
			<td>For tilling the soil in experimental plots</td>
		</tr>
		<tr >
			<td >S1000 ThermalCycler</td>
			<td >Sigma-Aldrich</td>
			<td >Custom-made</td>
			<td>For PCR amplification</td>
		</tr>
	</tbody>
</table>

quantification of the potential impact of glyphosate-based products on microbiomes

Glyphosate-based products (GBP) are the most common broad-spectrum herbicides worldwide. The target of glyphosate is the enzyme 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) in the shikimate pathway, which is virtually universal in plants. The inhibition of the enzyme stops the production of three essential amino acids: phenylalanine, tyrosine, and tryptophan. EPSPS is also present in fungi and prokaryotes, such as archaea and bacteria; thus, the use of GBP may have an impact on the microbiome composition of soils, plants, herbivores, and secondary consumers. This article aims to present general guidelines to assess the effect of GBP on microbiomes from field experiments to bioinformatics analyses and provide a few testable hypotheses. Two field experiments are presented to test the GBP on non-target organisms. First, plant-associated microbes from 10 replicated control and GBP treatment plots simulating no-till cropping are sampled and analyzed. In the second experiment, samples from experimental plots fertilized by either poultry manure containing glyphosate residues or non-treated control manure were obtained. Bioinformatics analysis of EPSPS protein sequences is utilized to determine the potential sensitivity of microbes to glyphosate. The first step in estimating the effect of GBP on microbiomes is to determine their potential sensitivity to the target enzyme (EPSPS). Microbial sequences can be obtained either from public repositories or by means of PCR amplification. However, in the majority of field studies, microbiome composition has been determined based on universal DNA markers such as the 16S rRNA and the internal transcribed spacer (ITS). In these cases, sensitivity to glyphosate can only be estimated through a probabilistic analysis of EPSPS sequences using closely related species. The quantification of the potential sensitivity of organisms to glyphosate, based on the EPSPS enzyme, provides a robust approach for further experiments to study target and non-target resistant mechanisms.

The aim of this protocol is to provide a general pipeline, from field experiments to bioinformatics analyses, that quantifies the potential sensitivity of organisms to the herbicide glyphosate. In Experiment 2 the average glyphosate concentration in the quail feed was 164 mg/kg and the average glyphosate concentration of the excreta samples (urine and fecal matter combined) was 199 mg/kg. Beddings collected from quails fed with GBP-contaminated feed had, on average, 158 mg/kg and control beddings measuring 0.17 mg/kg of glyphosate (Table 3). In the field experiments, plant species responded differently to glyphosate residues in the soils (section 1). Biomass of oat and turnip rape was greater in control soils compared to GBP-treated soils. However, faba beans and potato appeared to benefit from GBP treatment at the end of the growing season15. Glyphosate in poultry manure decreased plant growth in grass (Festuca pratensis) and strawberry (Fragaria x vescana) (section 1). The microbiota analyses from the field experiments have not yet been fully analyzed and are not presented here (section 2). The results of this protocol, when read either directly (as shown in sections 3 and 4) or indirectly (section 5), provide a measure of the proportion of potentially sensitive and resistant organisms to glyphosate in a dataset (Figure 9). The use of this method was tested with a collection of EPSPS protein sequences from microbial species of the core human gut microbiome that were obtained from public repositories12. In the study, 890 strains from the 101 most abundant bacterial species were analyzed with the EPSPSClass method to quantify the proportion of sensitive and resistant bacteria. The results showed that 54% of the species in the core human gut microbiome are potentially sensitive to glyphosate12. This trend is also observed in most of the prokaryotic world; additionally, in eukaryotes (mainly plants and fungi), the proportion of potentially sensitive species is even higher12. Moreover, we have utilized this method to quantify changes in sensitivity in the EPSPS protein at a microevolutionary level (Figure 10)14. We identified changes in sensitivity status in 12 out of 32 closely related groups of prokaryotes analyzed (Table 4)14. Thus, the continuous use of the GBPs may produce microbial dysbiosis (i.e., an imbalance of sensitive and resistant bacterial species) in plant, animal, and soil microbiomes. Moreover, it has been hypothesized that an increase in glyphosate-resistant bacteria may promote multidrug-resistant microbiomes14,41,42. Thus, this protocol sheds light on the interpretation of all these scenarios, as the EPSPS classification method provides a direct estimate of the intrinsic sensitivity of microbiomes to glyphosate. Due to the intrinsic sensitivity of the EPSPS protein to glyphosate is phylogenetically conserved14, it is possible to extrapolate the results from existing datasets into unknown microbiomes (Figure 8).
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/63109/63109fig01.jpg" /> 
Figure 1: General pipeline This is a general pipeline to analyze sensitivity to GBP from field experiments to bioinformatics analysis. <a href="https://www.jove.com/files/ftp_upload/63109/63109fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/63109/63109fig02.jpg" /> 
Figure 2: Field experiment 1 to test the effects of GBP residues on crop plant-associated microbes. The experimental field consists of alternating 10 control plots and 10 GBP treatment plots (23 m x 1.5 m) with 1.5 m buffer strips between plots. Two times a year since 2014, the GBP plots were treated with commercial GBP (glyphosate concentration 450 g L-1, application rate 6.4 L ha-1 in 5 L of tap water per plot) and the control plots with the same amount of tap water without glyphosate. The treatments were applied with a hand-operated pressure tank using a plastic hood in the sprinkler tip to protect GBPs from spreading outside the treatment plots. After a two-week safety period following the GBP application, oats (Avena sativa), faba beans (Vicia faba), and turnip rapes (Brassica rapa subsp. oleifera) were sown, and potatoes (Solanum tuberosum) were planted in the plots. Microbiota samples from the studied crop plants, leaves and roots, were collected several times since the start of the experiment in 2014. <a href="https://www.jove.com/files/ftp_upload/63109/63109fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/63109/63109fig03.jpg" /> 
Figure 3: Field experiment 2 tested the consequences of GBP residues in manure fertilizer for two perennial crops and their associated microbiota. Beddings collected from a 12-month aviary experiment with Japanese quails fed with control or GBP-contaminated feed were used as manure fertilizer in a field experiment. The experimental field consisted of 18 control and 18 GBP plots (1 m x 1 m) arranged in a 6 x 6 chessboard grid. The beddings were spread on the experimental field twice, in August 2018 and May 2019 (25 L / plot). Control plots were fertilized with beddings collected from quails fed with control feed and GBP plots with beddings from quails fed with GBP-contaminated feed. Glyphosate residues in control beddings were 0.17&#160;mg/kg of glyphosate and in GBP-bedding, the amount was 158 mg/kg of glyphosate. Two endophyte-symbiotic (E+), two endophyte-free (E-) Festuca pratensis, and two Fragaria x vescana were planted per plot in September 2018, approximately one month after the spread of the first beddings. Measurements of plant performance and fitness as well as sampling for root-and leaf-associated microbiota were conducted during two consecutive growing seasons (2019 &#38; 2020). <a href="https://www.jove.com/files/ftp_upload/63109/63109fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/63109/63109fig04.jpg" /> 
Figure 4: Analysis of the microbial taxa using 16S rRNA gene/ITS&#160;region and sensitivity of microbiomes to glyphosate using the EPSPS gene. (A) Analysis of 16S rRNA or ITS sequences to identify microbial taxa. (B) Analysis of EPSPS sequences to identify sensitivity of microbes to glyphosate (GS-glyphosate sensitive/GR-glyphosate resistant) <a href="https://www.jove.com/files/ftp_upload/63109/63109fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/63109/63109fig05.jpg" /> 
Figure 5: Algorithm to identify the class of EPSPS protein sequences. The input is an EPSPS protein sequence in FASTA format. The algorithm performs comparisons with known amino acid markers in reference protein sequences that determine the potential sensitivity to glyphosate. The algorithm was implemented at the freely accessible web server EPSPSClass29. <a href="https://www.jove.com/files/ftp_upload/63109/63109fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/63109/63109fig06.jpg" /> 
Figure 6: Basic inputs and outputs of the EPSPSClass web server. (A) Input: an EPSPS protein sequence in FASTA format. (B) Output 1 - identity: fraction of amino acid markers present in the query sequences (Classes I-IV)and motifs (Class III). (C) Output 2 - identity: alignments of the query and reference sequences. (D) Output 3 - pairwise alignments of the query and reference sequences. (E) Reference EPSPS sequences: Vibrio cholerae (vcEPSPS, class I), Coxiella burnetii (cbEPSPS, class II), Brevundimonas vesicularis (bvEPSPS, class III), Streptomyces davawensis (sdEPSPS, class IV). (F) Links to perform addition blastp searches and identification of conserved domains <a href="https://www.jove.com/files/ftp_upload/63109/63109fig06large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/63109/63109fig07.jpg" /> 
Figure 7: Access to pre-computed datasets of EPSPS sequences. Follow the indications in the figure to access the pre-computed dataset of EPSPS sequences. <a href="https://www.jove.com/files/ftp_upload/63109/63109fig07large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 8" class="xfigimg" src="/files/ftp_upload/63109/63109fig08.jpg" /> 
Figure 8: Example of how to estimate the potential sensitivity in microbiome projects without EPSPS sequences. The example uses values from the database of Alignable Tight Genomic Clusters30, which contains sequences from prokaryotic species. Hypothetical species from a microbiome project are Staphylococcus aureus, Corynebacterium diphtheriae, Campylobacter jejuni, Chlamydia psittaci and Sulfolobus islandicus. The sensitivity score to glyphosate is calculated as Number_Sensitive_Sequences/Total_Number_Of_Sequences. <a href="https://www.jove.com/files/ftp_upload/63109/63109fig08large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 9" class="xfigimg" src="/files/ftp_upload/63109/63109fig09.jpg" /> 
Figure 9: Scheme of the interpretation of the results from this protocol and hypothetical evolutionary scenarios. (A) In a microbiome, the proportion of potential sensitivity (in green) and resistance (in red) bacteria is approximately 50:50. Black dots denote microbial species unclassified; thus, their sensitivity to glyphosate is unknown. In some microbiomes, the proportion of sensitive bacteria is slightly higher, as in the human gut microbiome12. (B) Over time, the use of glyphosate may lead to microbial dysbiosis (i.e., an imbalance in the proportion of sensitive and resistant bacteria) leading to different hypothetical scenarios. (C) Hypothetical case 1 (no selection): The use of glyphosate does not influence the microbiome; thus, the proportion of sensitive and resistant bacteria remains constant. (D) Hypothetical case 2: The use of glyphosate removes bacteria sensitive to glyphosate from the population. We speculate that this scenario may be dose-dependent. (E) Hypothetical case 3: Selection pressure from the use of glyphosate enhances mutations in the EPSPS gene that change the sensitivity status of bacteria. Thus, the entire microbial population becomes resistant to glyphosate. Moreover, in this scenario, there might be an increase in multidrug-resistant bacteria. (F) Hypothetical case 4: the use of glyphosate alters the composition of certain bacterial species, producing an imbalance towards resistant bacteria, whereas some bacterial species remain unaltered, possibly due to additional resistant mechanisms such as efflux pumps or by overexpression of the EPSPS gene13. This scenario may also lead to an increase in glyphosate-resistant bacteria, as well as an increase in bacterial resistance to additional antibiotics. <a href="https://www.jove.com/files/ftp_upload/63109/63109fig09large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 10" class="xfigimg" src="/files/ftp_upload/63109/63109fig10v2.jpg" /> 
Figure 10: Distribution of the predicted sensitivity to glyphosate across the species tree. Pie charts indicate the proportion of species that are putatively sensitive (green) or resistant (red) to glyphosate, and unclassified (black). This figure has been adapted with permission from Rainio et al.14. <a href="https://www.jove.com/files/ftp_upload/63109/63109fig10largev2.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 11" class="xfigimg" src="/files/ftp_upload/63109/63109fig10.jpg" /> 
Figure 11: Inputs and outputs of the EPSPSClass webserver to test user&#39;s own reference sequence. (A) Input 1: query sequence. (B) Input 2: reference sequence. (C) Input 3: amino acid markers in the reference sequences. (D) Output: identity: fraction of amino acid markers in the query sequences (class I-IV and user&#39;s own reference sequences). <a href="https://www.jove.com/files/ftp_upload/63109/63109fig10large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Table 1: List of primers for PCR amplification of 16S rRNA gene and ITS region in microbiome analysis <a href="https://www.jove.com/files/ftp_upload/63109/Table 1-63109R2.xlsx" target="_blank">Please click here to download this Table.</a>
Table 2: Codes of the enzyme 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) in different databases <a href="https://www.jove.com/files/ftp_upload/63109/Table 2_63109R2.xlsx" target="_blank">Please click here to download this Table.</a>
Table 3: Average glyphosate concentration <a href="https://www.jove.com/files/ftp_upload/63109/Table 3-63109R2.xlsx" target="_blank">Please click here to download this Table.</a>
Table 4: Summary table of the percentage of species sensitive/resistant to glyphosate. This table has been adapted with permission from Rainio et al.14. <a href="https://www.jove.com/files/ftp_upload/63109/Table 4-63109R2.xlsx" target="_blank">Please click here to download this Table.</a>
Table 5: Positions of the amino acid markers in the reference sequences <a href="https://www.jove.com/files/ftp_upload/63109/Table 5-63109R2.xlsx" target="_blank">Please click here to download this Table.</a>

Watch this Scientific Journal Video about Quantification of the Potential Impact of Glyphosate-Based Products on Microbiomes at JoVE.com

Quantification of the Potential Impact of Glyphosate-Based Products on Microbiomes

Glyphosate-based products (GBP) are the most common broad-spectrum herbicides worldwide. In this article, we introduce general guidelines to quantify the effect of GBP on microbiomes, from field experiments to bioinformatics analyses.

Glyphosate-based products (GBP) are the most common broad-spectrum herbicides worldwide. The target of glyphosate is the enzyme ...

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3.9K Views.  University of Turku. Glyphosate-based products (GBP) are the most common broad-spectrum herbicides worldwide. In this article, we introduce general guidelines to quantify the effect of GBP on microbiomes, from field experiments to bioinformatics analyses.

Video: Quantification of the Potential Impact of Glyphosate-Based Products on Microbiomes

High-throughput Fluorometric Measurement of Potential Soil Extracellular Enzyme Activities

Microbes in soils and other environments produce extracellular enzymes to depolymerize and hydrolyze organic macromolecules so that they can be assimilated for energy and nutrients. Measuring soil microbial enzyme activity is crucial in understanding soil ecosystem functional dynamics. The general concept of the fluorescence enzyme assay is that synthetic C-, N-, or P-rich substrates bound with a fluorescent dye are added to soil samples. When intact, the labeled substrates do not fluoresce. Enzyme activity is measured as the increase in fluorescence as the fluorescent dyes are cleaved from their substrates, which allows them to fluoresce. Enzyme measurements can be expressed in units of molarity or activity. To perform this assay, soil slurries are prepared by combining soil with a pH buffer. The pH buffer (typically a 50 mM sodium acetate or 50 mM Tris buffer), is chosen for the buffer&#39;s particular acid dissociation constant (pKa) to best match the soil sample pH. The soil slurries are inoculated with a nonlimiting amount of fluorescently labeled (i.e. C-, N-, or P-rich) substrate. Using soil slurries in the assay serves to minimize limitations on enzyme and substrate diffusion. Therefore, this assay controls for differences in substrate limitation, diffusion rates, and soil pH conditions; thus detecting potential enzyme activity rates as a function of the difference in enzyme concentrations (per sample).
Fluorescence enzyme assays are typically more sensitive than spectrophotometric (i.e. colorimetric) assays,&#160;but can suffer from interference caused by impurities and the instability of many fluorescent compounds when exposed to light; so caution is required when handling fluorescent substrates. Likewise, this method only assesses potential enzyme activities under laboratory conditions when substrates are not limiting. Caution should be used when interpreting the data representing cross-site comparisons with differing temperatures or soil types, as in situ soil type and temperature can influence enzyme kinetics.

To measure potential rates of soil extracellular enzyme activities, synthetic substrates that are bound to a fluorescent dye are added to soil samples. Enzyme activity is measured as the fluorescent dye is released from the substrate by an enzyme-catalyzed reaction, where higher fluorescence indicates more substrate degradation.

Microbes in soils and other environments produce extracellular enzymes to depolymerize and hydrolyze organic macromolecules so that they can be ...

Methods for Facilitating Microbial Growth on Pulp Mill Waste Streams and Characterization of the Biodegradation Potential of Cultured Microbes

The kraft process is applied to wood chips for separation of lignin from the polysaccharides within lignocellulose for pulp that will produce a high quality paper. Black liquor is a pulping waste generated by the kraft process that has potential for downstream bioconversion. However, the recalcitrant nature of the lignocellulose resources, its chemical derivatives that constitute the majority of available organic carbon within black liquor, and its basic pH present challenges to microbial biodegradation of this waste material. Methods for the collection and modification of black liquor for microbial growth are aimed at utilization of this pulp waste to convert the lignin, organic acids, and polysaccharide degradation byproducts into valuable chemicals. The lignocellulose extraction techniques presented provide a reproducible method for preparation of lignocellulose growth substrates for understanding metabolic capacities of cultured microorganisms. Use of gas chromatography-mass spectrometry enables the identification and quantification of the fermentation products resulting from the growth of microorganisms on pulping waste. These methods when used together can facilitate the determination of the metabolic activity of microorganisms with potential to produce fermentation products that would provide greater value to the pulping system and reduce effluent waste, thereby increasing potential paper milling profits and offering additional uses for black liquor.

Industrial wastes can be collected and modified to analyze microbial growth. Lignocellulose extraction techniques provide components to analyze specific biodegradation ability. Gas chromatography-mass spectrometry identifies fermentation products of microorganisms grown on pulping waste. These methods determine the metabolic capacity of microorganisms to degrade pulping waste.

The kraft process is applied to wood chips for separation of lignin from the polysaccharides within lignocellulose for pulp that will produce a high ...

Exploring the Effects of Atmospheric Forcings on Evaporation: Experimental Integration of the Atmospheric Boundary Layer and Shallow Subsurface

Evaporation is directly influenced by the interactions between the atmosphere, land surface and soil subsurface. This work aims to experimentally study evaporation under various surface boundary conditions to improve our current understanding and characterization of this multiphase phenomenon as well as to validate numerical heat and mass transfer theories that couple Navier-Stokes flow in the atmosphere and Darcian flow in the porous media. Experimental data were collected using a unique soil tank apparatus interfaced with a small climate controlled wind tunnel. The experimental apparatus was instrumented with a suite of state of the art sensor technologies for the continuous and autonomous collection of soil moisture, soil thermal properties, soil and air temperature, relative humidity, and wind speed. This experimental apparatus can be used to generate data under well controlled boundary conditions, allowing for better control and gathering of accurate data at scales of interest not feasible in the field. Induced airflow at several distinct wind speeds over the soil surface resulted in unique behavior of heat and mass transfer during the different evaporative stages.

A protocol for the design and construction of a soil tank interfaced to a small climate controlled wind tunnel to study the effects of atmospheric forcings on evaporation is presented. Both the soil tank and wind tunnel are instrumented with sensor technologies for the continuous in situ measurement of environmental conditions.

Evaporation is directly influenced by the interactions between the atmosphere, land surface and soil subsurface. This work aims to experimentally study ...

Quantification of Heavy Metals and Other Inorganic Contaminants on the Productivity of Microalgae

Increasing demand for renewable fuels has researchers investigating the feasibility of alternative feedstocks, such as microalgae. Inherent advantages include high potential yield, use of non-arable land and integration with waste streams. The nutrient requirements of a large-scale microalgae production system will require the coupling of cultivation systems with industrial waste resources, such as carbon dioxide from flue gas and nutrients from wastewater. Inorganic contaminants present in these wastes can potentially lead to bioaccumulation in microalgal biomass negatively impact productivity and limiting end use. This study focuses on the experimental evaluation of the impact and the fate of 14 inorganic contaminants (As, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, Sb, Se, Sn, V and Zn) on Nannochloropsis salina growth. Microalgae were cultivated in photobioreactors illuminated at 984 &#181;mol m-2 sec-1 and maintained at pH 7 in a growth media polluted with inorganic contaminants at levels expected based on the composition found in commercial coal flue gas systems. Contaminants present in the biomass and the medium at the end of a 7 day growth period were analytically quantified through cold vapor atomic absorption spectrometry for Hg and through inductively coupled plasma mass spectrometry for As, Cd, Co, Cr, Cu, Mn, Ni, Pb, Sb, Se, Sn, V and Zn. Results show N. salina is a sensitive strain to the multi-metal environment with a statistical decrease in biomass yieldwith the introduction of these contaminants. The techniques presented here are adequate for quantifying algal growth and determining the fate of inorganic contaminants.

Integration of microalgal cultivation with industrial flue gas will ultimately introduce heavy metals and other inorganic compounds into the growth media. This study presents a procedure used to determine the end fate and impact of heavy metals and inorganic contaminants on the growth of Nannochloropsis salina grown in photobioreactors.

Increasing demand for renewable fuels has researchers investigating the feasibility of alternative feedstocks, such as microalgae. Inherent advantages ...

Preparation of DMMTAV and DMDTAV Using DMAV for Environmental Applications: Synthesis, Purification, and Confirmation

Dimethylated thioarsenicals such as dimethylmonothioarsinic acid (DMMTAV) and dimethyldithioarsinic acid (DMDTAV), which are produced by the metabolic pathway of dimethylarsinic acid (DMAV) thiolation, have been recently found in the environment as well as human organs. DMMTAV and DMDTAV can be quantified to determine the ecological effects of dimethylated thioarsenicals and their stability in environmental media. The synthesis method for these compounds is unstandardized, making replicating previous studies challenging. Furthermore, there is a lack of information about storage techniques, including storage of compounds without species transformation. Moreover, because only limited information about synthesis methods is available, there may be experimental difficulties in synthesizing standard chemicals and performing quantitative analysis. The protocol presented herein provides a practically modified synthesis method for the dimethylated thioarsenicals, DMMTAV and DMDTAV, and will help in the quantification of species separation analysis using high performance liquid chromatography in conjunction with inductively coupled plasma mass spectrometry (HPLC-ICP-MS). The experimental steps of this procedure were modified by focusing on the preparation of chemical reagents, filtration methods, and storage.

Preparation of DMMTAV and DMDTAV Using DMAV for Environmental Applications: Synthesis, Purification, and Confirmation

This article presents modified experimental protocols for dimethylmonothioarsinic acid (DMMTAV) and dimethyldithioarsinic acid (DMDTAV) synthesis, inducing dimethylarsinic acid (DMAV) thiolation through mixing of DMAV, Na2S, and H2SO4. The modified protocol provides an experimental guideline, thereby overcoming limitations of the synthesis steps that could have caused experimental failures in quantitative analysis.

Dimethylated thioarsenicals such as dimethylmonothioarsinic acid (DMMTAV) and dimethyldithioarsinic acid (DMDTAV), which are produced by the metabolic ...

Quantification of Endogenous Auxin and Cytokinin During Internode Culture of Ipecac

Adventitious shoot formation is an important technique for the propagation of economically important crops and for the regeneration of transgenic plants. Phytohormone treatment is required for the induction of adventitious shoots in most species. Whether adventitious shoots can be induced is determined by the balance between auxin and cytokinin (CK) levels. Much effort goes into determining optimum concentrations and combinations of phytohormones in each tissue used as explants and in each plant species. In ipecac, however, adventitious shoots can be induced on internodal segments in culture medium without phytohormone treatment. This allows the inherent plasticity of ipecac for cell differentiation to be evaluated. To induce adventitious shoots in ipecac, we cultured internodal segments at 24 &#176;C under 15 &#181;mol m&#8722;2 s&#8722;1 of light in a 14-h light/10-h dark cycle on phytohormone-free B5 medium solidified with 0.2% gellan gum for 5 weeks. To investigate phytohormone dynamics during adventitious shoot formation, we measured endogenous indole-3-acetic acid and CKs in the segments by liquid chromatography-tandem mass spectrometry LC-MS/MS. This method allows analysis of endogenous indole-3-acetic acid and CKs levels in a simple manner. It can be applied to investigate the dynamics of endogenous auxin and CK during organogenesis in other plant species.

Adventitious shoots can be induced on internodal segments of ipecac without phytohormone treatment. To evaluate phytohormone dynamics during adventitious shoot formation, we measured endogenous auxin and cytokinin in internodal segments by LC-MS/MS.

Adventitious shoot formation is an important technique for the propagation of economically important crops and for the regeneration of transgenic plants. ...

The Effect of the Application of Thyme Essential Oil on Microbial Load During Meat Drying

Meat is a high protein meal that is used in the preparation of jerky, a popular food snack, where preservation and safety are important. To assure food safety and to extend the shelf life of meat and meat products, the use of either synthetic or natural preservatives have been applied to control and eliminate foodborne bacteria. A growing interest in the application of natural food additives for meat has increased. Microorganisms, such as Escherichia coli, contaminate meat and meat products, causing foodborne illnesses. Therefore, it is necessary to improve the meat conservation process. However, the use of essential oils when the meat is being dried has not been deeply studied. In this regard, there is an opportunity to increase the value of dried meat and reduce the risk of foodborne illnesses by applying essential oils during the drying process. In this protocol, we present a novel method of applying thyme essential oil (TEO) during meat drying, specifically in vapor form directly in a drying chamber. For evaluation, we use Minimal Inhibitory Concentration (MIC) to detect the number of harmful bacteria in the treated samples compared to raw samples. The preliminary results show that this method is a viable and alternative option to synthetic preservatives and that it significantly reduces microbial load in dried meat.

Microorganisms such as Escherichia coli that contaminate meat products cause foodborne illnesses. The use of essential oils in the meat drying process has not been deeply studied. Here, we present a novel method of applying thyme essential oil to meat during drying to reduce the microbial load in dried meat.

Meat is a high protein meal that is used in the preparation of jerky, a popular food snack, where preservation and safety are important. To assure food ...

The Hawaii Protocol for Scientific Monitoring of Coffee Berry Borer: a Model for Coffee Agroecosystems Worldwide

Coffee berry borer (CBB) is the most devastating insect pest for coffee crops worldwide. We developed a scientific monitoring protocol that is aimed at capturing and quantifying the dynamics and impact of this invasive insect pest as well as the development of its host plant across a heterogeneous landscape. The cornerstone of this comprehensive monitoring system is timely georeferenced data collection on CBB movement, coffee berry infestation, mortality by the fungus Beauveria bassiana, and coffee plant phenology via a mobile electronic data recording application. This electronic data collection system allows field records to be georeferenced through built-in global positioning systems, and is backed by a network of weather stations and records of farm management practices. Comprehensive monitoring of CBB and host plant dynamics is an essential part of an area-wide project in Hawaii to aggregate landscape-level data for research to improve management practices. Coffee agroecosystems in other parts of the world that experience highly variable environmental and socioeconomic factors will also benefit from implementing this protocol, in that it will drive the development of customized integrated pest management (IPM) to manage CBB populations.

Comprehensive monitoring of coffee berry borer and host plant dynamics is essential for aggregating landscape-level data to improve management of this invasive pest. Here, we present a protocol for scientific monitoring of coffee berry borer movement, infestation, mortality, coffee plant phenology, weather, and farm management via a mobile electronic data recording application.

Coffee berry borer (CBB) is the most devastating insect pest for coffee crops worldwide. We developed a scientific monitoring protocol that is aimed at ...

Xylem Water Distribution in Woody Plants Visualized with a Cryo-scanning Electron Microscope

A scanning electron microscope installed cryo-unit (cryo-SEM) allows specimen observation at subzero temperatures and has been used for exploring water distribution in plant tissues in combination with freeze fixation techniques using liquid nitrogen (LN2). For woody species, however, preparations for observing the xylem transverse-cut surface involve some difficulties due to the orientation of wood fibers. Additionally, higher tension in the water column in xylem conduits can occasionally cause artifactual changes in water distribution, especially during sample fixation and collection. In this study, we demonstrate an efficient procedure to observe the water distribution within the xylem of woody plants in situ&#160;by using a cryostat and cryo-SEM. At first, during sample collection, measuring the xylem water potential should determine whether high tension is present in the xylem conduits. When the xylem water potential is low (&#60; ca. &#8722;0.5 MPa), a tension relaxation procedure is needed to facilitate better preservation of the water status in xylem conduits during sample freeze fixation. Next, a watertight collar is attached around the tree stem and filled with LN2&#160;for freeze fixation of the water status of xylem. After harvesting, care should be taken to ensure that the sample is preserved frozen while completing the procedures of sample preparation for observation. A cryostat is employed to clearly expose the xylem transverse-cut surface. In cryo-SEM observations, time adjustment for freeze-etching is required to remove frost dust and accentuate the edge of the cell walls on the viewing surface. Our results demonstrate the applicability of cryo-SEM techniques for the observation of water distribution within xylem at cellular and subcellular levels. The combination of cryo-SEM with non-destructive in situ observation techniques will profoundly improve the exploration of woody plant water flow dynamics.

Observing the water distribution within the xylem provides significant information regarding water flow dynamics in woody plants. In this study, we demonstrate the practical approach to observe xylem water distribution in situ&#160;by using a cryostat and cryo-SEM, which eliminates artifactual changes in the water status during sample preparation.

A scanning electron microscope installed cryo-unit (cryo-SEM) allows specimen observation at subzero temperatures and has been used for exploring water ...

Measurement of the Potential Rates of Dissimilatory Nitrate Reduction to Ammonium Based on 14NH4+/15NH4+ Analyses via Sequential Conversion to N2O

The importance of understanding the fate of nitrate (NO3&#8722;), which is the dominant N species transferred from terrestrial to aquatic ecosystems, has been increasing because global nitrogen loads have dramatically increased following industrialization. Dissimilatory nitrate reduction to ammonium (DNRA) and denitrification are both microbial processes that use NO3&#8722; for respiration. Compared to denitrification, quantitative determinations of the DNRA activity have been carried out only to a limited extent. This has led to an insufficient understanding of the importance of DNRA in NO3&#8722; transformations and the regulating factors of this process. The objective of this paper is to provide a detailed procedure for the measurement of the potential DNRA rate in environmental samples. In brief, the potential DNRA rate can be calculated from the 15N-labeled ammonium (15NH4+) accumulation rate in 15NO3&#8722; added incubation. The determination of the 14NH4+ and 15NH4+ concentrations described in this paper is comprised of the following steps. First, the NH4+ in the sample is extracted and trapped on an acidified glass filter as ammonium salt. Second, the trapped ammonium is eluted and oxidized to NO3&#8722; via persulfate oxidation. Third, the NO3&#8722; is converted to N2O via an N2O reductase deficient denitrifier. Finally, the converted N2O is analyzed using a previously developed quadrupole gas chromatography&#8211;mass spectrometry system. We applied this method to salt marsh sediments and calculated their potential DNRA rates, demonstrating that the proposed procedures allow a simple and more rapid determination compared to previously described methods.

Measurement of the Potential Rates of Dissimilatory Nitrate Reduction to Ammonium Based on 14NH4+/15NH4+ Analyses via Sequential Conversion to N2O

A series of methods to determine the potential DNRA rate based on 14NH4+/15NH4+ analyses is provided in detail. NH4+ is converted into N2O via several steps and analyzed using quadrupole gas chromatography&#8211;mass spectrometry.

The importance of understanding the fate of nitrate (NO3&#8722;), which is the dominant N species transferred from terrestrial to aquatic ecosystems, has ...