prone to wind and water erosion (Chen et al., 2006). Xiao et al. (2015) cul- tured moss crusts artificially on the Loess Plateau, China, and monitored the effects on soil stabilization as well as water infiltration and retention over eight years. The results indicate a positive impact, however, the effect on the sur- face water conditions was only negligible (Xiao et al., 2015). BSCs are also sources of biotechnological products such as the microbial sunscreen scytone- min (Siezen, 2011). As mentioned in Section 1.2.1, BSCs occupy extremely cold environments such as the Arctic and Antarctica (Williams et al., 2017). These cold-adapted and cold-acclimated organisms possess unique features in terms of transcriptome, proteome and lipidome (Jung et al., 2014). In order to cope with low temperatures and freezing, they produce antifreeze proteins (AFPs) which can be biotechnologically exploited (Jung et al., 2014). AFPs can be added to red blood cells to prevent hemolysis during freeze-thaw cycles or to food, such as meat and ice cream, to reduce ice crystal size (Jung et al., 2014).
1.5
Methodology
Studying BSC communities involves a plethora of methods as they may be analyzed in an ecological context as well as in terms of biodiversity and func- tionality (Borchhardt et al., 2017b; Liu et al., 2014; Williams et al., 2017). There are non-invasive methods, which can be carried out in the field, but most techniques involve sampling and further analysis of the material in a lab- oratory (Belnap et al., 2001b; Borchhardt et al., 2017a; Rajeev et al., 2013).
There are three different methods commonly used to assess the BSC cover along a transect in a certain area: Quadrats, line-point intercept and line in- tercept (Belnap et al., 2001b; Bowker et al., 2013; Williams et al., 2017). Each methodology has advantages and drawbacks and the choice should be depen- dent on the degree of accuracy and detail required (Belnap et al., 2001b). Within these predefined sampling areas, so-called vegetation plots, either in- dividual taxa or morphological groups are determined (Belnap et al., 2001b;
1.5. METHODOLOGY CHAPTER 1. INTRODUCTION
Castillo-Monroy et al., 2016). The classification of morphological groups is quick, simple and gives information about the ecological role (Belnap et al., 2001b; Williams et al., 2017). The identification of taxa, on the other hand, is more precise but in the field it is limited to bryophytes and lichens (Bel- nap et al., 2001b; Bowker et al., 2013; Castillo-Monroy et al., 2016; Chiquoine et al., 2016). Microorganisms, such as Cyanobacteria and algae, have to be sampled and analyzed in the laboratory (Borchhardt et al., 2017a; Chiquoine et al., 2016). Portable devices enable researches to measure several parameters directly in the field (Colesie et al., 2016). Colesie et al. (2016), for example, monitored the activity of BSCs using an IMAGING-PAM and a gas exchange system, both portable.
Sampled BSC material can be analyzed in different ways. Commonly, soil properties, such as carbon, nitrogen, phosphorus, sulfur, sand, silt and clay content as well as pH, are determined (Baumann et al., 2017; Borchhardt et al., 2017a; Bowker et al., 2013; Castillo-Monroy et al., 2016). Moreover, the chlorophyll a, EPS and scytonemin concentration are measured giving infor- mation about biomass, crust stability and stage of development, respectively (Belnap et al., 2008; Chiquoine et al., 2016; Couradeau et al., 2016; Kuske et al., 2012). In order to study nutrient cycles, activity assays of key enzymes, such as phosphatase, urease, invertase and catalase, are carried out (Bowker et al., 2013; Liu et al., 2014). However, collecting BSC samples also enables the identification of microorganisms inhabiting the crust (Borchhardt et al., 2017a; Chiquoine et al., 2016; Williams et al., 2016). Using light microscopy, a great variety of taxa can be identified either directly in the sample or after the preparation of enrichment cultures and isolates (Baumann et al., 2017; Borchhardt et al., 2017a; Cameron and Devaney, 1970; Williams et al., 2016). This type of identification is based on the recognition of morphological traits such as color, cell size and shape, or motility (Ab Majid et al., 2015; Cox, 1996; John et al., 2002; Lányi, 1988). For instance, Borchhardt et al. (2017a) isolated eukaryotic microalgae from BSCs by cultivating them on agar plates and used the morphological key by Ettl and Gärtner (2014) to identify the taxa. Despite
CHAPTER 1. INTRODUCTION 1.5. METHODOLOGY
this method being relatively fast and cheap, morphological features are often ambiguous and, thus, difficult to identify (Albrecht et al., 2017; Manoylov, 2014; Misawa, 1999). Molecular techniques, such as barcoding, offer a reliable alternative (Vieira et al., 2016; Wang et al., 2016). A barcode is a molecular marker gene, such as the 16S/18S ribosomal ribonucleic acid (rRNA) gene and the internal transcribed spacer (ITS) region, the ribulose-1,5-bisphosphat carboxylase/oxygenase (RuBisCO) large subunit or the cytochrome c oxidase I (COX1), which is amplified and sequenced (An et al., 1999; Doyle et al., 1997; Evans et al., 2007; Wilmotte, 1994). Commonly, these amplified prod- ucts are sequenced using the chain-termination method originally developed by Sanger et al. (1977). The resulting sequence can be identified by perform- ing a sequence homology search against a suitable database (Altschul et al., 1990; Raja et al., 2017). However, these databases can contain incorrect and wrongly annotated sequences or even lack the reference sequence required for identification (Taberlet et al., 2012). To circumvent this problem, the query sequence may be combined with an appropriate taxon sampling and analyzed using e.g. maximum parsimony or maximum likelihood based phylogenetic inference methods (Komárek et al., 2014; Mount, 2008; Wang et al., 2016).
Culture isolates also provide the possibility to perform physiological ex- periments with BSC organisms. For example, typical abiotic stressors, which are prevailing in terrestrial habitats (e.g. high radiation, drought), can be mimicked and the effects recorded (Herburger and Holzinger, 2015; Holzinger et al., 2009; Karsten and Holzinger, 2014). A recent study by Herburger and Holzinger (2015) compared the physiological response to desiccation stress of different Klebsormidium and Zygnema strains. Additionally, underlying molec- ular mechanisms can be studied by using approaches such as transcriptomics or proteomics (Carniel et al., 2016; Holzinger et al., 2014; Wang et al., 2009a). Proteomic studies focus on all proteins of an organism at a certain time, which constantly change in response to environmental conditions, while transcrip- tomics are based on gene expression levels (Han et al., 2008; Liang and Zeng, 2016). For transcriptomic studies, total ribonucleic acid (RNA) is isolated
1.5. METHODOLOGY CHAPTER 1. INTRODUCTION
and transcribed into complementary deoxyribonucleic acid (cDNA) which is subsequently sequenced using next-generation sequencing (NGS) tools such as Illumina or Roche 454 (Bentley et al., 2008; Holzinger et al., 2014; Liang and Zeng, 2016; Margulies et al., 2005). The raw data is filtered and ex- pression levels are determined using different software, e.g. the R package Bioconductor (Liang and Zeng, 2016). If annotations for the differentially ex- pressed genes (DEGs) are available, conclusions on functional relations can be drawn (Carniel et al., 2016; Holzinger et al., 2014; Liang and Zeng, 2016). Ideally, physiological data is also recorded and used for comparison and val- idation (Iñiguez et al., 2017). Holzinger et al. (2014), for example, studied the desiccation stress response of the streptophyte Klebsormidium crenulatum using the effective quantum yield of photosystem II as a fitness parameter and transcriptomics to shed light on the molecular mechanisms.
Unfortunately, most organisms inhabiting natural habitats, such as BSCs, are unculturable and, thus, cannot be studied individually as described above (Massana et al., 2014; Schloss and Handelsman, 2005; Shi et al., 2009; Ward et al., 1990). Furthermore, the interactions between all organisms within a community should also be considered for a holistic understanding (Urich et al., 2014). A barcode amplicon (e.g. the 16S rRNA gene) can be produced from the whole community and used in a metabarcoding approach, either cloned into vectors and sequenced using the chain-termination technique, or directly ap- plied to a NGS platform (Couradeau et al., 2016; Eldridge et al., 2015; Fierer, 2017; Fiore-Donno et al., 2017; Frey et al., 2013; Kuske et al., 2012). The latter is also referred to as amplicon sequencing and can give insights into biodiver- sity and relative abundance of individual organisms in a sample (Lange et al., 2015; Taberlet et al., 2012). The generated sequences are counted, normalized and annotated to obtain the percentage per taxa, also known as operational taxonomic unit (OTU) (Caporaso et al., 2010; Couradeau et al., 2016; Fiore- Donno et al., 2017; Taberlet et al., 2012). To minimize spurious OTUs and overestimation, a so-called mock community, which is an artificial sample with known diversity and abundance, should be included in the sequencing run