• Ешқандай Нәтиже Табылған Жоқ

next-generation sequencing and imaging flow

N/A
N/A
Protected

Academic year: 2023

Share "next-generation sequencing and imaging flow"

Copied!
62
0
0

Толық мәтін

This led to the emergence of several distinct saline and hypersaline water reservoirs, such as the Small Aral Sea, the Western Aral Sea and Chernyshev Bay. This study is focused on: 1) the characterization of the epilimnion phytoplankton and bacterioplankton communities of the Chernyshev Bay and northern parts of the Western Aral Sea, and 2) the correlation of phytoplankton and bacterioplankton biodiversity with the set of environmental variables (e.g. temperature, conductivity, salinity, pH and nutrient concentration). To achieve this, water samples were collected from the Chernyshev Bay and the Western Aral Sea (expedition Aral-2022), which were further analyzed by full-length 16S rRNA next-generation sequencing (NGS) for bacterioplankton diversity, and imaging flow cytometry (IFC) for phytoplankton diversity.

NGS-based taxonomic analysis of the bacteriome showed that there is a diversity difference between Chernyshev Bay and the West Aral Sea and strong similarity between coastal and limnetic points in Chernyshev Bay. The patterns described here represent the first observation of bacteriome and phytoplankton distribution in Chernyshev Bay and western Aral parts of the former Aral Sea.

Introduction

Literature review

  • Aral Sea disaster
  • Aral Sea stratification
  • Aral Sea biodiversity
  • Phytoplankton investigation methods
  • Bacterioplankton investigation method

From the data obtained in 2015, the stratified layers were present in the Western Aral Sea and Chernyshev Bay (Izhitskaya et al., 2019). 10 of the tectonic plates, providing the supply of water that varies in its consistency (Jarsjö and Destouni, 2004; Oberhänsli et al., 2007; Boehrer and Schultze, 2008). These dramatic changes created an endemic environment and affected the biodiversity of the Aral Sea (Izhitskiy et al., 2016; Shurigin et al., 2019).

One of the IFC tools is FlowCAM (Yokogawa Fluid Imaging Technologies, USA), the instrument that combines cytometry- and microscopy-based analysis (Dashkova et al., 2017; Stauffer et al., 2019). On the other hand, Oxford Nanopore (UK)-based platforms use longer reads that allow researchers to identify microbiome community diversity, but it has a higher error rate compared to Illumina (USA) (Nygaard et al., 2020; Mirasbekov et al. .al., 2021; Egeter et al., 2022; Meirkhanova, 2022).

Figure 1. The change of Aral Sea profile: A) change over the last 6 decades (Aladin et al., 2018) B) the  satellite image of Aral Sea territory taken on August 19, 2019, by Landsat 7 (the picture was used with the
Figure 1. The change of Aral Sea profile: A) change over the last 6 decades (Aladin et al., 2018) B) the satellite image of Aral Sea territory taken on August 19, 2019, by Landsat 7 (the picture was used with the

Hypothesis

Aims

Materials and Methods

Rationale

Experimental plan

  • Water sample collection
  • Hydrochemistry analysis
    • Phosphorous content analysis
    • Nitrogen content analysis
  • Imaging flow cytometry analysis
  • Next-generation sequencing
    • DNA extraction
    • Library construction
    • Nanopore-based Sequencing
    • Raw data analysis
  • Statistical analysis
  • Permits and approvals

The absorbance of the reddish complex was measured using the YSI 9500 Photometer (USA) at 500 nm and was proportional to the amount of nitrite ions. The reddish complex concentration was measured using the YSI 9500 Photometer (USA) at 500 nm and was proportional to the amount of nitrite ions initially present in the sample. The FlowCAM instrument (Yokogawa Fluid Imaging Technologies, USA) was calibrated according to the manufacturer's protocol, followed by the process of data collection from the fluid samples.

According to the protocol, the samples were lysed by vortexing in the lysis buffer containing glass beads. Extracted DNA will be stored in Eppendorf tubes (Germany) at -20oC. The process of library preparation for DNA sequencing started with PCR amplification.

Results

  • Water samples collection
  • Hydrochemistry analysis
  • Phytoplankton analysis by IFC
  • Bacterioplankton analysis by NGS
    • Read quality assessment
    • Taxonomical analysis of bacterioplankton
  • Statistical analysis
    • α-Diversity analysis of bacterioplankton diversity
    • NMDS analysis of bacterioplankton diversity
    • PCA analysis of the environmental parameters

Since points WA1 and WA2 had the highest pH values, this may indicate that the West Aral Sea had higher alkalinity compared to the Chernyshev Bay. On the other hand, points of the Western Aral Sea showed lower values ​​of conductivity, 182.1 for WA1 and 181.2 for WA2, which may represent a slightly lower values ​​of conductivity of Western Aral Sea, compared to Chernyshev Bay. In general, the graphical data did not show a discernible pattern or trend, but the values ​​of ammonium concentrations in the West Aral Sea were slightly lower mg/L) than in the Chernyshev Bay mg/L).

Based on the IFC results, Chernyshev Bay water samples showed a higher number of phytoplankton cells compared to Vestaral Lake samples (23 - 139). Potentially, this indicates that total phytoplankton diversity was higher in Chernyshev Bay than in the western Aral Sea. 22. With the exception of CH_LIM_6 (264 genera) and CH_LIM_7 (277 genera), the average number of genera in Chernyshev Bay limnetic points was approx. 403.

The visual analysis of the heat map indicates high similarity in biodiversity and relative abundance of genera across all 11 points of Chernyshev Bay. The graph shows the total number of bacterioplankton genera over 13 locations in the Chernyshev Bay and the Western Aral Sea. Heat map showing the relative abundance of top 15 most abundant bacterioplankton genera across 13 locations in the Chernyshev Bay and Western Aral Sea.

The graph of percentage abundance of chitin-degrading bacteria genera in the Chernyshev Bay and Western Aral Sea. For the Simpson analysis, excluding the WA1 point where the index was equal to 0.76, the rest of the points showed approximately identical index values ​​for the Chernyshev Bay and the Western Aral Sea, ranging from 0.79 to 0.82. On the other hand, the Simpson index's stress usually comes only from common, and because the main genera only involve 5 groups (Spiribacter, Halopeptonella, Halanaerobacter, Salinibacter and Halomonas), the index values ​​were almost identical. Bar charts of α-diversity analysis of the Chernyshev Bay and the Western Aral Sea: A) Shannon index;.

All points were color-coded according to their geographical location, blue for Chernyshev Bay and red for the Western Aral Sea. As seen in the NMDS, points WA1 and WA2 were separated from the rest of the data set, indicating that there is a large difference in diversity between the Western Aral Sea and Chernyshev Bay.

Table 2. Summarized hydrochemistry dataset.
Table 2. Summarized hydrochemistry dataset.

Discussion

  • Analysis of hydrochemistry trends of the Chernyshev Bay and West Aral Sea
  • IFC based phytoplankton taxonomy analysis
  • NGS based bacterioplankton taxonomy analysis
  • Statistical confirmation of hypothesis
  • Limitations

The increase in temperature and consequent global warming may be the cause of the acidification trend of Asian water reservoirs (Jamshidi and Bin Abu Bakar, 2011; Dutta et al., 2021). Similar to the studies by Makkaveev et al. 2016), this work includes an analysis of total phosphorus concentration in the littoral and limnetic zones. In general, it manifests itself as a tendency to increase the total concentration of phosphorus; however, it remains questionable why there was such a significant change between 2016 and 2022 (Makkaveev et al., 2016).

The concentration can be measured by alternative methodologies of total nitrogen concentration measurement (e.g. Kjeldahl digestion, persulfate oxidation) (Raveh and Avnimelech, 1979; Andrei et al., 2015). Similar results were obtained by Heidelberg et al. 2013) during analysis of phytoplankton abundance over hypersaline Lake Tyrrell, where they stated that Dunaliella spp. For example, in the works of Chen et al. 2009), the glycerol-3-phosphate dehydrogenase (G3pgh) may be responsible for the tolerance mechanism.

Another later work suggested that the system-to-salt response depends on the early and late reactions and found a link between a photosystem component (psaA, psaB, psbB, psbC), several chaperones (HSP70B, HSP90A) and ATP synthase subunits (atpA). , atpB, atpE) to salt stress regulation (Wang et al., 2019). The presence of filamentous cyanobacteria was largely described in studies of the Small Aral Sea, but no relevant data on the Western Aral Sea and Chernyshev Bay (Orlova and Rusakova, 1999; Komárek, 2012; Klimaszyk et al., 2022). Spiribacter and Halopeptonella are members of the Gammaproteobacteria class and belong to the same family of Ectothiorhodospiraceae (Shurigin et al., 2019; León et al., 2020).

Halomonas is also a member of the Gammaproteobacteria class, but it belongs to a different family called Halomonadaceae (Begmatov et al., 2020; Hu et al., 2021). Both the coastal and limnetic zones of Chernyshev Bay had a high abundance of Halanaerobacter and Salinibacter, which belong to the classes Halanaerobiia and Rhodothermata, respectively (Taroepratjeka et al, 2021; . Viver et al., 2023). These bacterioplankton genera have been extensively studied for their potential roles in a variety of biogeochemical processes (e.g., arsenic cycling, sulfur cycling, and carbon fixation) (Paul et al., 2016; Edwardson and Hollibaugh, 2018).

Conclusions and Future Directions

An alternative solution could be the use of a fluorescence-activated mode, where the scientist can narrow the image collection to the organism of interest (Alvarez et al., 2013; Dashkova et al., 2017). This limitation comes because IFC itself is a semi-automated method and may be reduced as it moves towards more automated image analysis (Blaschko et al., 2005; Drews et al., 2013; Dashkova et al., 2017). Next, during the NGS, there are several potential sources of limitations that can be categorized as follows: 1) Nanopore sequence limitation and 2) database limitation. As mentioned above, Nanopore-based sequencing uses long reads, but the reading of electrical signal during the sequencing is prone to the errors, which can affect the results (Winand et al., 2019; Egeter et al., 2022; Meirkhanova, 2022 ).

The problem is the necessity of its constant updating, which sometimes causes certain problems, such as the lack of the possibility of growing the species in laboratory conditions or the absence of the species in the relevant database (Malashenkov et al., 2021).

Significance, and application…

Non-metric multidimensional scaling (NMDS) ordination of Chernyshev Bay (blue) and West Aral Sea (red) sample points based on the Bray-Curtis dissimilarity indices. Evolution of sea level of the Great Aral Sea from satellite altimetry and its implications for water balance. Hydrophysical state of the Great Aral Sea in autumn 2013: Thermal structure, currents and internal waves.

Current state of the Aral Sea: diverse physical and biological characteristics of the remaining basins, Scientific Reports. Onshore soil microbes and endophytes respond differently to geochemical and mineralogical changes in the Aral Sea. Spatial heterogeneity of chemistry of the small Aral Sea and the Syr Darya River and its impact on plankton communities.

Sequence of Aral Sea ecosystems during the transition from oligohaline to polyhaline water body. Climate variability over the past 2000 years and past economic and irrigation activities in the Aral Sea Basin. Past, present and future of the Aral Sea - An overview of its fauna and flora before and during the regression crisis.

Main results of observations of changes in bottom biota and ichthyofauna of the Great Aral Sea in the period 2002–2017. A look at the prokaryotic diversity of the great Aral Sea reveals new extremophilic bacterial and archaeal groups. Calculation of electrical conductivity of water of the Aral Sea and correction of the sound salinity from 2002-2009.

Protocol links

Summary of reagents and resources

Supplementary tables

Supplementary figures

An example (CH_LIT_1) of phylogenetic analysis of the most numerous genera in the coastal zone of Chernyshev Bay. An example (CH_LIM_1) of phylogenetic analysis of the most numerous genera in the limnetic zone of Chernyshev Bay.

Figure S2.  An example (CH_LIT_1) of phylogenetic analysis of the most abundant genera in the Chernyshev  Bay’s littoral zone
Figure S2. An example (CH_LIT_1) of phylogenetic analysis of the most abundant genera in the Chernyshev Bay’s littoral zone

Сурет

Figure 1. The change of Aral Sea profile: A) change over the last 6 decades (Aladin et al., 2018) B) the  satellite image of Aral Sea territory taken on August 19, 2019, by Landsat 7 (the picture was used with the
Figure 2. Schematic overview of the experimental process.
Table 1. Summary of the collected samples’ location.  *
Table 2. Summarized hydrochemistry dataset.
+7

Ақпарат көздері

СӘЙКЕС КЕЛЕТІН ҚҰЖАТТАР

Then the creep curve for the material of polyether polymer concrete will be described by the equation ϕε =σ = 348.9·ε Experimental and design values of the creep strain of the