​Quantification and Microbial Diversity Analysis of Ruminal Methanogenic Populations in Indian Gir Native Cattle

R. Karunakaran1, V. Yuvachandran Viva1, P. Raja1,*, M. Parthiban1
1Department of Animal Biotechnology, Madras Veterinary College, Tamil Nadu Veterinary and Animal Sciences University, Chennai-600 007, Tamil Nadu, India.
Background: Methane emission from the ruminants is receiving global attention due to its global warming potential. It imposes the development of cost-effective and easily adoptable energy to reduce methane emissions from ruminants. Apart from this, the information available on the methanogenic microflora and their populations in the Indian native cattle is also very limited. In this study, the normal methanogenic microflora of Indian native Gir cattle was studied using molecular methods and compared with cross breed cattles.

Methods: The rumen fluid was collected and DNA isolation was carried out from Gir, Gir cross and Kangayam crossbred cattle. The partial 16S rRNA and mcrA gene amplification were carried out by PCR and further subjected to sequence analysis. Further, Methanogenic population in the ruminal fluid were analyzed by SYBR Green-based real-time PCR.

Result: This study provides a basic understanding of the normal methanogenic microfloral diversity and their population in the Gir native cattle of Indian origin compared with cross breed cattle.
There are various microbial communities that exist in the rumen and it forms a complex system that includes bacteria, protozoa, archaea and fungi. In this microbial community, bacterial populations are highest and diverse in nature. Rumen microorganisms play an important role in the emission of a greenhouse gas called methane. Methane occupies the second-largest gas that contributes to the greenhouse gas which is primarily produced by ruminants. Globally, about 80 million tonnes of methane are produced annually from enteric fermentation mainly from ruminants out of which Indian livestock contributes about 15.1% of total global enteric methane emission (Patra et al., 2014). As the demand for meat and milk continues to grow worldwide especially in developing countries, methane emission from ruminants will likely continue to increase in the years to come unless effective and practical methane mitigation strategies are implemented in ruminant feeding. Over the past decade, intensive research has been carried out all over the world to identify and develop effective and practical means to decrease the methane emission from ruminants (Hristov et al., 2013).
       
In India there are 37 different indigenous breeds of cattle and 13 different indigenous breeds of buffalo are available. Among cattle breed, the Gir cattle is known for its milk producing quality which has one of the principle zebu breeds originating in India. Kangayam cattle breeds are known for drought which is found in Tamil Nadu. These two cattle breeds are very much suitable for milk and drought in India which has also been cross bred with different cattle bred to increase the milk production and for other purposes. When compared to exotic cattle and their cross bred, native cattle produce 5-8% less methane by enteric fermentation.
       
The present study was undertaken to ascertain the methanogenic archaeal diversity and their population in the rumen of Gir, Gir cross and Kangayam cross bred by16S rRNA and mcrA gene sequencing and their population quantification by quantitative real time PCR.
 
Cattle, diet and rumen sample collection
 
A 100-200 ml of rumen fluid was collected from Gir, Gir cross and Kangayam cross bred cattle maintained at Livestock Farm Complex (LFC), Madhavaram milk colony, Chennai, Tamil Nadu by rumen fluid extraction pump. The rumen fluid was collected in an anaerobic container and then transferred to a separate sterile container, labelled and transported to laboratory and stored at -20°C until further analysis. All the animals were fed with standard milch cattle ration. 
 
DNA extraction
 
Total bacterial DNA from the rumen fluid of all the gir, gir cross and kangayam cross bred were extracted using qiagen DNA stool kit as per the manufacturer instructions. The quantification and purity of the extracted DNA was measured at A260/280 using nanodrop spectro photometer.
 
PCR amplification of 16S rRNA and mcrA gene
 
The PCR amplification of partial 16S rRNA gene was carried out with an initial denaturation for 5 min at 94°C, 30 cycles at 94°C for 30 s, 57°C for 1 min, 72°C for 1 min and final elongation for 7 min at 72°C and PCR amplification of mcrA gene was carried out with an initial denaturation for 3 min at 95°C, 30 cycles at 95°C for 30 s, 55°C for 30 s, 72°C for 1 min and final elongation for 5 min at 72°C.The reaction was performed for the total volume of 25 µl which consist of 1 µl of forward and reverse primer (20 pmol concentration), 12.5 µl of master mix, 3 µl of DNA template and 7.5 µl of nuclease free water (NFW). The amplified PCR product were analysed in 1.2% agarose gel containing ethidium bromide under gel documentation unit. The primers used for PCR and real time PCR details were given in Table 1.

Table 1: Primers used in this study for PCR and qRT-PCR analysis.


 
Sequencing and phylogenetic analysis
 
The PCR amplified products of partial 16S rRNA and mcrA gene were purified using Qiagen PCR gel purification kit and sequencing was performed at Eurofins genomics sequencing Ltd, Bengaluru, India. The nucleotide sequence data was subjected to BLAST analysis (www.ncbi.nlm.nih. gov), assembled are analyzed and using seq man and mega align programs of lasergene package version 7.1.0. Nucleotide sequence alignment was performed by Clustal W method with Mega Align program and predicted amino acid sequence was analysed by proteon program of DNA Lasergene (DNA star Inc). Phylogenetic analysis of 16S rRNA and mcrA gene sequence was performed using maximum likelihood method with 1000 bootstrap replication in the MEGA software Version 10. The reference sequences used for construction of phylogenetic analysis are given in Table 2.

Table 2: Reference sequence used in this study for phylogenetic analysis.


 
qRT-PCR analysis of methanogenic bacterial populations
 
The selected methanogenic bacterial populations were determined by calculating the copy number of 16S rRNA genes. Three pair of primers was used to detect Methanobrevibactersp, Methanosphaera stadtmane and total methanogens from rumen samples.
       
qRT- PCR was performed using SYBR green master mix with the total reaction volume of 10 µl in each well in triplicate. The reaction volume consists of 5 µl of SYBR green master mix, 0.5 µl (5 pmol) of forward and reverse primer, 3 µl of nuclease free water (NFW) and 1 µl of DNA template. Copy number of a DNA was calculated using serially diluted DNA and used as standard in the quantification. The qRT- PCR was performed using the real time PCR system (Applied Biosystems) with the initial denaturation 95°C for 10 min, which is followed by 40 cycles at 95°C for 30 s, 60°C for 30 s and 72°C for 35 s. For melt curve analysis, the temperature was increased 0.3°C every 20 s from 60°C and 95°C. The standard DNA curve were constructed by methanogenic species specific primers based on the serial dilution of standard DNA. The copy number of the standard DNA was calculated using the following formula:
 
 
 
Where,
X is amount of DNA in nanograms (ng).
N is the length of DNA in basepairs (bp).
6.022 × 1023 is Avogadro constant and 660 g/mole is average mass of 1 bp dsDNA.
       
This research was carried out in Department of Animal Biotechnology, Madras veterinary college for period of 1year (2021).
 
The cattle population in India has been increasing from 190.90 million in 2012 to 192.50 million in 2019 (Agricultural Research Data Book, 2019). Basic understanding about rumen methanogens microbial diversity in indigenous and exotic cattle is important to formulate the strategies for methane mitigation from Indian livestock. In the present study, diversity of methanogens is explored in the Gir native cattle along with crossbred cattle of Gir and Kangayam bred fed with standard milch animal diet using molecular approaches based on 16S rRNA and mcrA gene. To the best of our knowledge, it is the first report on the methanogens microbial diversity analysis in Indian Gir native cattle along with crossbred cattle of Gir and Kangayam.
 
PCR amplication and sequence analysis
 
The partial 16S rRNA gene of methanogenic bacteria of ruminal fluid from Gir, Gir cross and Kangayam cross bred was amplified using the methanogenic specific 16S rRNA primers with product size of 800 bp and sequenced (MW916668- MW916670 ) (Fig 1). There are several reports about the use of 16S rRNA gene for the identification of methanogens from environmental samples. The 16S rRNA gene sequence of all the three strains of methanogenic producing bacteria from Gir, Gir cross and Kangayam cross revealed 99-100% identity with other KX787709, KX787608 and HQ616028, respectively. The phylogenetic analysis also revealed that, all these three strains of 16S rRNA from Gir, Gir cross and Kangayam Cross were claded with EU330421 and M59142, which are methanogenic bacteria earlier reported from India which indicates our all the three strains belongs to Methanobacteriales (Fig 3). The phylogeny of methanogens determined using mcrA sequences in accordance with those determined using 16S rRNA gene sequences (Friedrich, 2005).

Fig 1: PCR amplification of 16s rRNA gene of Gir, Gir Cross and Kangayam cross.



Fig 3: Phylogenetic analysis of 16S rRNA gene sequence of Gir, Gir cross and Kangayam cross bred cattle.


       
However, the use of 16S rRNA is imposes the risk of amplification of other bacteria along with Methanogenic bacteria. It is essential to detect the methanogens on the basis of functional genes that are found to be unique in methanogenesis. The Methyl coenzyme M. reductase (mcr) is the terminal enzyme involved in methanogenesis, which reduces the methyl group bond of methyl coenzyme M with the release of methane (Friedrich, 2005). Because the a-subunit of mcr(mcrA) and its isoenzyme gene (mrtA) are highly conserved among methanogens and that these genes are almost exclusively found in methanogens, mcrA/mrtA-based detection of methanogens has been used.
       
Further in this study, mcrA gene of methanogenic specific bacteria of ruminal fluid from Gir, Gir cross and Kangayam cross bred was amplified using specific primers with the product size of 470 bp (Fig 2) and sequenced (MW757257, MW767001 and MW767003).The sequence analysis revealed that the all the sequence of mcrA gene has more than 99 percentage of identity with AB928466, AB615893 and AB617118 for Gir, Gir cross bred and Kangayam cross bred. The phylogenetic analysis of mcrA gene forms three different clade in which all the three sequences belongs to Methanomicrobiales along with AF414044 (Wiltshire SP40JG, UK), HQ450171 (Haryana, India) and HQ450167 (Haryana, India) (Fig 4). Comparative studies between the 16S rRNA and mcrA gene revealed mcrA gene is more efficient for classifying the diverse group of methanogens in phylogenetically (Juottonen et al., 2006, Jerman et al., 2009).

Fig 2: PCR amplification of mcrA gene of Gir, Gir Cross and Kangayam cross.



Fig 4: Phylogenetic analysis of mcrA gene sequence of Gir, Gir cross and Kangayam cross bred cattle.


       
Our findings revealed the dominance of Methanobrevibacter-related sequences on the basis of 16S rRNA and mcrA gene sequence homology. The presence of Methanobrevibacter as major phylotype in the Gir cattle, Gir cross bred and Kangayam cross bred is in agreement with earlier reports of Denman et al., (2007) who reported Methanobrevibacter sp. are the dominant methanogens in Brahman crossbred steers (Bosindicus). In another study, Jeyanathan et al., (2011) revealed that Methanobrevibacter sp. are dominant in cattle from New Zealand. Franzolin et  al. (2012) have also identified Methanobrevibacter as the dominant genus in Holstein cattle, water buffaloes and crossbred buffalo, respectively. Dominance of genus Methanobrevibacter observed in our study is in accordance to Janseen and Kirs. (2008) who surveyed that 61.6% of the rumen archaea belongs to this genus. Skillman et al. (2006) and Wright et al. (2007) have reported the presence of M. stadtmanae in bovine rumen. The majority of the sequences retrieved from bovine rumens and cattle dung are belongs to Methanomicrobiales and Methanobacteriales Rastogi et al. (2008). On the other hand, the same group observed that in Surti rumen 16S rRNA library, 97% clones were related to Methanomicrobiales and Methano bacteriales. Many studies are also carried out based on the 16s rRNA gene sequences due to their highly conserved nature and availability of the sequences from databases. However, based on the 16S rRNA sequence analysis it is very difficult to differentiate closely related taxons. Recently, studies were being carried out with mcrA gene instead of 16s rRNA gene since the mcrA has higher evolutionary rate, less conserved sequences and can also afford information related to the functional diversity of methanogens (Sheppard et al., 2005). For these properties of mcrA gene it’s used as a marker for phylogenetic analysis in conjunction with or independent of, 16S rRNA genes (Steinberg and Regan, 2008).  
       
Montoya et al. (2011) reported the number of differences per site in the mcrA gene fragment is 2-3 times higher than that in the full length 16S rRNA and therefore, mcrA sequences offers conclusive resolution and assignment of genera than 16S rRNA gene sequences (Meyer and Kuever, 2007). Overall, the findings from the present study indicate that methanogenic populations of Gir cattle and the crossbred of Gir and Kangayam cattle are predominant with Methanobrevibacter related phylotypes. The diversity analysis using mcrA gene has provided better insight of
rumen methanogens than 16S rRNA gene.
 
Per cent identity of mcr agene
 
The mcrA gene reveals 92%, 92.5% and 95.9% percent identity to Gir, Gir cross and Kangayam cross bred with AF414044 and AF414044 respectively. Among the three mcrA gene sequences, Gir cattle reveals 100% identity with Kangayam cross and 99.8% identity with Gir cross bred (Table 3).

Table 3: Per cent identity of mcrA gene of Gir, Gir cross and Kangayam cross bred.


 
Deduced amino acids variations
 
The deduced amino acid variations of mcrA gene reveals, there are 57 amino acid variations while comparing with GU385700. The amino acid changes are conserved across Gir, Gir cross and Kangayam cross bred, however it varies for all other mcrA gene of methanogenic bacteria. The deduced amino acid variation was shown in Table 4. 

Table 4: Deduced amino acid variations of mcrA protein.


 
Absolute quantification of methanogenic population of ruminal fluid by qRT-PCR
 
The total methanogen population, Methanobrevibacter sp. and Methanosphaera stadtmanae from the ruminal fluid of three cattle from each bred of Gir, Gir cross and Kangayam cross were analyzed using absolute quantification by real time PCR. This study reveals that the total methanogen populations of all the three Gir cattle is 0.26 mg/ml, 1.95 mg/ml and 0.31mg/ml, Gir cross is 0.23 mg/ml, 0.26 mg/ml and 0.44 mg/ml and for Kangayam cross is 4.91mg/ml, 5.08 mg/ml and 5.78mg/ml respectively. The absolute copy number of partial 16S rRNA gene of Methanosphaera stadtmanae of all the three Gir cattle is 0.63 mg/ml, 1.12 mg/ml and 0.29 mg/ml, Gir cross is 0.17 mg/ml, 0.02 mg/ml and 0.38 mg/mlandfor Kangayam cross is 5.15 mg/ml, 5.94 mg/ml and 7.36 mg/ml respectively. This confirming more or less similar quantity of methanogen in the ruminal fluid. The absolute copy number of Methanobrevibacter sp. of partial 16S rRNA gene of all the three gir cattle is 2.12 mg/ml, 2.18 mg/ml and 1.17 mg/ml, gir cross cattle is 0.29 mg/ml, 0.31 mg/ml and 0.55 mg/ml and for kangayam cross cattle are 5.66 mg/ml, 6.16 mg/ml and 7.17 mg/ml respectively (Table 5). This confirming more or less similar quantity of methanogens in the ruminal fluid.

Table 5: Absoulte quantificaton and statistical analysis of total methanogens, M. stadtmanae and Methanobrevibacter sp from Gir, Gir corss and Kangayam cross cattle.


       
The proportions of 16S rRNA genes of Methanobrevibacter sp. and Methanosphaera stadtmanae, the later reveals higher significance difference between these two methanogenic bacteria in the ruminal fluid of Gir, Gir cross and Kangayam cross.
       
Our results of qRT-PCR analysis revealed that the Methanobrevibactersp is the most dominant gene in rumen and Methanosphaera stadtmanae copy numbers are very low level in the rumen total methanogens. The unique combination of ruminal microbiota in each animal may have important roles in the host’s nutrient uptake and energy metabolism, phenotypes that are usually regulated by the genetics, diet and environment of the host.
 
 
This study was funded by Indian Council of Agricultural Research (ICAR) scheme on “Estimation of methane emission under different feeding systems and development of mitigation strategies” function in the Department of Animal Nutrition, Madras Veterinary College, Chennai-07.
 
The authors declare that they have no conflict of interest.
 

  1. Agricultural Research Data Book. Indian Agricultural Statistics Research Institute, ICAR. http://www.iasri.res.in/agridata/ 12data/HOME_12.HTML.

  2. Denman, S.E., Tomkins, N. and McSweeney, C.S. (2007). Quantitation and diversity analysis of ruminalmethanogenic populations in response to the antimethanogenic compound bromochloromethane. FEMS Microbiol. Ecol. 62: 313-322. https://doi.org/10.1111/j.1574-6941.2007. 00394.x.

  3. Franzolin, R., St-Pierre, B., Northwood, K. and Wright, A.D.G. (2012). Analysis of rumen methanogen diversity in water buffaloes (Bubalus bubalis) under three different diets. Microb. Ecol. 64: 131-139. DOI: 10.2307/41489794.

  4. Friedrich, M.W. (2005). Methyl-coenzyme M reductase genes: Unique functional markers for methanogenic and anaerobic methane-oxidizing Archaea. Methods Enzymol. 397: 428- 442. https://doi.org/10.1016/S0076-6879(05) 97026-2.

  5. Hristov, A.N., Oh, J., Lee, C., Meinen, R., Montes, F. and Ott, F. (2013). In: Mitigation of Greenhouse Gas Emissions in Livestock Production. A Review of Options for Nnon- CO2 Emissions. [Gerber, P.J., Henderson, B., Makkar, H.P.S. (eds.)], Rome: FAO, pp. 226.

  6. Jeyanathan, J., Kirs, M., Ronimus, R.S., Hoskin, S.O. and Janssen, P.H. (2011). Methanogen community structure in the rumens of farmed sheep, cattle and red deer fed different diets. FEMS Microbiol. Ecol. 76: 311-326. https://doi.org/ 10.1111/j.1574-6941.2011.01056.x.

  7. Juottonen, H., Galand, P.E. and Yrjala, K. (2006). Detection of methanogenicArchaeain peat: comparison of PCR primers targeting the mcrAgene. Res Microbiol. 157: 914- 921. https://doi.org/10.1016/j.resmic.2006.08.006.

  8. Klieve, A.V., Ouwerkerk, D. and Maguire, A.J. (2012). Archaea in the foregut of macropod marsupials: PCR and amplicon sequence based observations. Journal of Applied Microbiology. 113(5): 1065-1075. https://doi.org/10.1111/ j.1365-2672.2012.05428.x.

  9. Meyer, B. and Kuever, J. (2007). Molecular analysis of the diversity of sulfate-reducing and sulfur-oxidizing prokaryotes in the environment, using aprA as functional marker gene. Appl. Environ. Microbiol. 73: 7664-7679. https://doi.org/10.11 28/AEM.01272-07.

  10. Montoya, L., Lozada-Chavez, I., Amils, R., Rodriguez, N. and Marín, I. (2011). The sulfate-rich and extreme saline sediment of the ephemeral tirez lagoon: A biotope for acetoclasticsulfate-reducing bacteria and hydrogenotrophic methanogenic archaea. Int. J.Microbiol. 2011. 753-758. https://doi.org/10.1155/2011/753758.

  11. Narihiro, T. and Sekiguchi, Y. (2011). Oligonucleotide primers, probes and molecular methods for the environmental monitoring of methanogenicarchaea. Microbial biotechnology. 4(5): 585-602.  https://doi.org/10.1111/ j.1751-7915.2010.00239.x.

  12. Patra, A.K. and Yu, Z. (2014). Combinations of nitrate, saponin and sulfate additively reduce methane production by rumen cultures in vitro while not adversely affecting feed digestion, fermentation or microbial communities. Bioresource Technology. 155: 129-135. https://doi.org/ 10.1016/j.biortech.2013.12.099.

  13. Rastogi, G., Ranade, D.R., Yeole, T.Y., Gupta, A.K., Patole, M.S. and Shouche, Y.S. (2008). Molecular analyses of methanogen diversity associated with cattle dung. World J. Microbiol. Biotechnol. 24: 2973-2979. https://doi.org/ 10.1007/s11274-008-9840-1.

  14. Sheppard, S.K., McCarthy, A.J., Loughnane, J.P., Gray, N.D., Head, I.M. and Lloyd, D. (2005). The impact of sludge amendment on methanogens community structure in an upland soil. Appl. Soil Ecol. 28: 147-162. https://doi.org/ 10.1016/j.apsoil.2004.07.004.

  15. Sirohi, S.K., Chaudhary, P.P., Singh, N., Singh, D. and Puniya, A.K. (2013). The 16S rRNA and mcrA gene based comparative diversity of methanogens in cattle fed on high fibre based diet. Gene. 523(2): 161-166. https:// doi.org/10.1016/j.gene.2013.04.002.

  16. Skillman, L.C., Evans, P.N., Strompl, C. and Joblin, K.N. (2006). 16S rDNA directed PCR primers and detection of methanogens in the bovine rumen. Letters in Appl. Microbiol. 42(3): 222-228. https://doi.org/10.1111/j.1472- 765X.2005.01833.x.

  17. Steinberg, L.M. and Regan, J.M. (2008). Phylogenetic comparison of the methanogenic communities from an acidic, oligotrophic fen and an anaerobic digester treating municipal wastewater sludge. Appl. Environ. Microbiol. 74: 6663-6671. https://doi.org/10.1128/AEM.00553-08.

  18. Wright, A.D.G., Auckland, C.H. and Lynn, D.H. (2007). Molecular diversity of methanogens in feedlot cattle from Ontario and Prince Edward Island, Canada. Appl. Environ. Microbiol. 73: 4206-4210. https://doi.org/10.1128/ AEM.00103-07.

  19. Zhou, M.I. and Hernandez-Sanabria, E. (2009). Assessment of the microbial ecology of ruminal methanogens in cattle with different feed efficiencies. Appl. Environ. Microbiol. 75(20): 6524-6533. https://doi.org/10.1128/AEM.02815-08.

Editorial Board

View all (0)