Chapter 08: Whole Cell Identification of Microorganisms in their Natural Environment with Fluorescence in situ Hybridization (FISH)

Chapter 8:

Supplementary files for chapter 8: Whole Cell Identification of Microorganisms in their Natural Environment with Fluorescence in situ Hybridization (FISH)

The FISH pipeline

List of contents:

1. Step 1: Introduction – two gateways for selection of suitable FISH procedure
2. Step 2: General identification of cells, irrespective of their function

a: Choose type of ribosomal gene target

b: Gene probe search

c: Probe match

d: Create reference gene sequence database

e: Evaluation of gene sequence database

f: Design gene probe(s)

g: Theoretical (in silico) evaluation of newly designed gene probes

h: Select fluorochromes for gene probes

i: Order gene probes

j: Probe evaluation

k: Trouble-shooting

3. Step 3: Sophisticated identification of cells and their function

a: activity and in situ physiology

b: quantification

c: other genes than ribosomes

d: microbial interactions

e: high amount of samples

1. Step 1, Introduction - two gateways for selection of suitable FISH procedure:

Since the late 1980s, a plethora of different FISH procedures have been developed. Many parameters have to be considered for a successful FISH experiment, such as research objective(s), sampling parameters (including the state and the concentration of the organisms and the background to be investigated), selection of appropriate gene targets and FISH procedure, to combination with other analytical procedures and instruments. Several reviews on FISH have been published throughout the last two decades, focusing either on general issues, (e.g. Amann and Fuchs, 2008; Wagner et al., 2003; Wagner et al., 2006; Wagner and Haider 2012) or on specific ecosystems (e.g. wastewater treatment (Nielsen et al., 2009), soil (Schmid et al., 2006), geobiology (Lee et al., 2011), for applications in food and clinical sciences, see e.g. Frickman et al., 2017, Liehr 2009 and 2017, Rohde et al., 2015, Volpi and Bridger 2008).

Principally, all FISH procedures can be divided into two main categories:

• General identification of cells, irrespective of their function → step 2

• Sophisticated identification of cells and their function → step 3

Each of these contain several options to either solve different types of problems or to retrieve additional information by sophisticated analyses of additional parameters – these will be described briefly under each category.

2. Step 2: General identification of cells, irrespective of their function

2a) Choose type of ribosomal gene target

• 16S/23S rRNA for prokaryotes

• 18S/28S rRNA for eukaryotes

• ISR/IST for prokaryotes and eukaryotes

2b) Gene probe search

Search for published gene probes in ProbeBase (Greuter et al., 2016, http://probebase.csb.univie.ac.at/), which contains many published gene probes and some PCR primers. Complement with literature search. If no gene probes are available, proceed to d) to design gene probes.

2c) Probematch

Perform Probematch on selected gene probes by selecting the testprobe functions on online genedatabases like the Silva (Quast et al., 2013, https://www.arb-silva.de/search/testprobe/) and the RDP (Cole et al., 2014, https://rdp.cme.msu.edu/probematch/search.jsp), or on own gene databases if available (e.g. by using the bioinformatics software package ARB, Westram et al., 2011, http://www.arb-home.de/). Check if the optimal concentration of formamide at 46° C for stringent hybridization has been determined. If the probe is out of date and stringent conditions have not been performed, proceed to 2d), otherwise continue to 2g).

2d) Create reference gene sequence database

Prior to ProbeDesign: create a reference gene sequence database from online gene databases, and if available, from own gene sequence studies. Examples of online reference gene sequence databases:

• Curated databases with culturable and unculturable species in the databases by Silva (Quast et al., 2013, https://www.arb-silva.de/search/) and RDP (Cole et al., 2014, https://rdp.cme.msu.edu/hierarchy/hb_intro.jsp).

• Database with only culturable species, the Living Tree Project (Yarza et al., 2010): https://www.arb-silva.de/projects/living-tree/.

• Database for type species, the Ezbiocloud (Yoon et al., 2017): http://www.ezbiocloud.net/taxonomy.

• Database with rRNA operon numbers (Stoddard et al., 2015): https://rrndb.umms.med.umich.edu/.

• Database for intergenic transcribe spacer (ITS) gene sequences for fungi (Nilsson et al., 2015; Irinyi and Meyer 2015, http://its.mycologylab.org/)

2e) Evaluation of gene sequence database

Check alignments and improve where necessary. Reconstruct phylogenetic trees. Select suitable clades for probe design.

2f) Design gene probe(s)

Gene probe can be designed with different softwares, however most so far published gene probes have been designed with the software package ARB (Westram et al., 2011, http://www.arb-home.de/; for more detailed descriptions on probe design, see Lee et al., 2011).

2g) Theoretical (in silico) evaluation of newly designed gene probes

• Perform Probematch on designed probes as described in 2c), in order to select suitable candidates for further testing.

• Perform computational evaluation of RNA-targeted FISH probes using MATH-FISH (Yilmaz et al., 2011, http://mathfish.cee.wisc.edu/).

• Where appropriate, screen for non-target binding at off target sites containing single nucleotide insertions or deletions at LOOPOUT, http://www.ribosome.org/loopout.html.

2h) Select fluorochromes for the gene probes

Select suitable fluorochromes based on the filter set up and laser type of the microscope, and where appropriate sample type (to avoid confounding background). Examples of weblinks: (e.g. http://www.abcam.com/secondary-antibodies/fluorochrome-chart-a-complete-guide; https://www.zeiss.com/microscopy/int/service-support/filtersets-dyes.html).

2i) Order gene probes

Suggestion of companies: Biomers (recommended: http://www.biomers.net/), or Molecular Probes/Invitrogen, MWG Biotech, Operon, Sigma, Thermo Hybaid. Dissolve freeze-dried probes in a suitable buffer of appropriate pH according to manufacturer´s instructions, aliquot probes and store safely.

2j) Probe evaluation

Evaluate the gene probes experimentally by first using the standard oligonucleotide FISH protocol (Amann 1995, see description in the manuscript, section 8.5). Determine optimal formamide concentration with a formamide series (Amann and Schleifer, 2001). If possible, use a digital image software for a quantitative evaluation, e.g. the daime software (Daims 2009, http://dome.csb.univie.ac.at/daime). Perform tests on suitable pure cultures, mixed samples, or on clones (CLONE-FISH, Schramm et al., 2002).

2j) Trouble-shooting

Examples of problems: low amount of cells, low probe signal intensity, confounding background. Examples of solution options with the standard oligonucleotide FISH procedure: optimize sampling and fixation procedure, optimize pretreatment (e.g. enzymatic) of cells prior to the FISH procedure, increase probe concentration, prolong hybridization time, change to another ribosomal gene target. If these options will not help, change FISH procedure, depending on research objective, choose between:

• Simple, fast procedures to increase the probe signal intensity: DOPE-FISH (e.g. Behnman et al., 2012), HELPER FISH (Fuchs et al., 2000), PNA-FISH (e.g. Perry-O´Keefe et al., 2001), Quantum-dot FISH (e.g. Fei et al., 2016).
• Time-consuming but efficient procedure to increase the probe signal intensity: Polynucleotide FISH (e.g. Pernthaler et al., 2002a), CARD-FISH (e.g. Yamaguchi et al., 2015), QUAL probes (Sando and Kool 2002; Silverman and Kool 2005; MiL-FISH (Schimak et al., 2015).
• To increase the specificity, change to LNA FISH (e.g. Kubota et al., 2006a; Priya et al., 2012), or use QUAL probes (Sando and Kool 2002; Silverman and Kool 2005).
• To avoid confounding background: Change fluorochrome, increase probe signal intensity of targeted cells as suggested above, or employ spectral imaging (e.g. Ainsworth et al., 2006).

Step 3: Sophisticated identification of cells and function

Step 3a: Activity and function

For exploration of activity and function in combination with FISH, different combinations with other analytical procedures and instruments have been explored. Depending on the research objectives and access to suitable laboratory facilities, different categories have been developed:

• General activity measurements:

o Gene probe signal intensity comparisons (e.g. Rossetti et al., 2007).

o Activity dyes (e.g. Nielsen et al., 2003).

o Precursor 16S rRNA gene probes (Oerther et al., 2000).

o Internal transcriber spacer (ITS) probes (e.g. Schmid et al., 2001).

o Specific enzyme activities (e.g. Xia et al., 2007).

• Addition of substrates to support growth or reagents to induce stress (e.g. Ouverney and Fuhrmann 1997)

• Incubation with radioactive compounds to explore uptake patterns by cells:

o Incubation with 3H-thymidine or bromodeoxyuridine (BrdU) in combination with FISH to detect DNA-synthesizing cells (e.g. Pernthaler et al., 2002b; Cottrell and Kirchman 2003).

o Microautoradiography in combination with FISH (MAR-FISH) – allows detection of uptake of different substrates labelled with e.g. 3H or 14C (e.g. Nielsen and Nielsen 2010).

• Incubation with stable isotopes to explore sophisticated uptake patterns by cells:

o nanoSIMS in combination with FISH (e.g. Musat et al., 2016).

o nanoSIP, a combination of stable isotope probing, nanoSIMS and FISH (e.g. Musat et al., 2012, Polerecky et al., 2012).

o RAMAN-FISH/RAMAN-MAR-FISH, for simultaneous cultivation-independent identification and determination of incorporation of stable isotopes or radioactive compounds into microbial cells (e.g. Wagner 2009; Eichhorst et al., 2016; Wang et al., 2016).

• Tracking of protein synthesis in individual microorganisms, BON-CAT FISH (Hatzenpichler et al., 2014; 2016).

• Detection of specific non-ribosomal genes and mRNA (see section 3c).

• Combination with immunofluorescent probes, to enable simultaneous detection and enumeration of bacterial populations with distinct 16S rRNA gene sequences and/or surface markers of interest (Gmür and Lüthi-Schaller 2007).

• Combination with electron microscopy, GOLD-FISH etc. (e.g. Gérard et al., 2005; Ye at al., 2015; Schmidt and Eichhorst, 2016).

Step 3b: Quantification

FISH targeted cells can be quantified either with regard to the amount of probe targeted cells, or with regard to the probe signal intensity (e.g. Fuchs et al., 1998; Daims, 2009). Quantifications can be performed manually by microscope observation, by digital image analysis, or by flow cytometry.

• Digital image analysis (see manuscript for further descriptions):

o Daime software - for direct counting based on cell area/volume (Daims 2009, http://cshprotocols.cshlp.org/content/2009/7/pdb.prot5253.full.)

o Spike FISH – for creation of a calibration curve for translation of cell area/volume data to cell concentration (Daims et al., 2001).

• Flow cytometry – for fast analysis of multiple samples or to explore the probe signal intensity of different probes (e.g. Fuchs et al., 1998; Neuenschwander et al., 2015).

Step 3c: Other gene targets

Traditionally, successful FISH relies on a high copy number of the target gene, such as the ribosomes. Since the last decade, several new types of FISH procedures have emerged which can also target low copy genes, such as housekeeping genes or functional genes. These procedures are generally much more tedious and time-consuming, but the obvious benefit of these is that they can generate more sophisticated and detailed information. So far, only few types of non-ribosomal gene targets have been used for FISH procedures. Unfortunately, neither online gene probe bases for other gene targets than ribosomes nor curated databases similar to the Silva or the RDP database for ribosomal genes (exception FunGene, FISH et al., 2013, http://fungene.cme.msu.edu/) are available. For probe design, gene sequences must therefore be downloaded from general public databases and more thoroughly processed. Examples of FISH procedures for visualization of other genes than ribosomal genes:

For prokaryotes or eukaryotes:

• CARD-FISH; mRNA FISH (e.g. Pernthaler and Amann, 2004; Kubota et al., 2006a; Coleman et al., 2007; Pilhofer et al., 2009; Zeller et al., 2016).

• RING-FISH (Zwirglmaier 2006; Pratscher et al., 2009).

• Different types of in situ cycling in amplification procedures: (Kenzaka et al., 2005; Maruyama et al., 2005, Smolina et al., 2007, see review by Wagner and Haider 2012).

• “Gene FISH” (Moraru et al., 2010; Barrero-Canosa et al., 2017).

For viruses:

• Clinically relevant viruses (e.g. Chou et al., 2013).

• Phage-FISH (e.g. Dang et al., 2014).

For enrichment of specific probe-targeted cells for further gene sequencing:

• Flow cytometry and whole genome amplification (e.g. Haaron et al., 2013; Kalyuzhnaya et al., 2006).

• Magneto-FISH (e.g. Trembath-Reichert et al., 2013; 2016).

• Polynucleotide FISH (e.g. Zwirglmaier 2005).

Step 3d: Microbial interactions

One of the main benefits of FISH is that associations between different organisms can be visualized with ribosomal targeted gene probes. However, such probes cannot reveal the activity state nor the physiology or relations of the identified species. Thus, several sophisticated FISH procedures have been developed to enable this, e.g. by developing a way to visualize substrate uptake as listed in step 2a. Detailed reviews on such advanced approaches are described in e.g. Orphan 2009, Dekas et al., 2016 and Musat et al., 2016.

Step 3e: High amount of samples or species

Many FISH applications are evaluated by microscopy, however, this is a tedious and time consuming procedure, especially if the microbial diversity and the amount of samples is high. Thus, non-microscope based procedures have been developed to simplify and speed up the analyses. These procedures are based on e.g. flow cytometry (e.g. Neuenschwander et al., 2015), microarray technology (e.g. the phylochip, deSantis et al., 2007; Taylor et al., 2010) or spectral imaging, CLASI-FISH (Valm et al., 2013) and MiL-FISH (Schimak et al., 2015).

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