Profiling of bacterial and fungal communities of Mexican cheeses by high throughput DNA sequencing

Accepted Manuscript Profiling of bacterial and fungal communities of Mexican cheeses by high throughput DNA sequencing

Selvasankar Murugesan, Maria Paulina Reyes-Mata, Khemlal Nirmalkar, Alejandra Chavez-Carbajal, Josue Isaac JuarezHernandez, Rosario Erea Torres-Gomez, Alberto Pina-Escobedo, Otoniel Maya, Carlos Hoyo-Vadillo, Emma Gloria RamosRamírez, Juan Alfredo Salazar-Montoya, Jaime Garcia-Mena PII: DOI: Reference:

S0963-9969(18)30561-1 doi:10.1016/j.foodres.2018.07.023 FRIN 7763

To appear in:

Food Research International

Received date: Revised date: Accepted date:

23 April 2018 5 July 2018 14 July 2018

Please cite this article as: Selvasankar Murugesan, Maria Paulina Reyes-Mata, Khemlal Nirmalkar, Alejandra Chavez-Carbajal, Josue Isaac Juarez-Hernandez, Rosario Erea Torres-Gomez, Alberto Pina-Escobedo, Otoniel Maya, Carlos Hoyo-Vadillo, Emma Gloria Ramos-Ramírez, Juan Alfredo Salazar-Montoya, Jaime Garcia-Mena , Profiling of bacterial and fungal communities of Mexican cheeses by high throughput DNA sequencing. Frin (2018), doi:10.1016/j.foodres.2018.07.023

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ACCEPTED MANUSCRIPT Profiling of Bacterial and Fungal communities of Mexican Cheeses by High Throughput DNA Sequencing Selvasankar Murugesana,# [email protected];

Maria

Paulina

Nirmalkara,b,#

Khemlal

[email protected];

Reyes-Mataa

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[email protected]; Alejandra Chavez-Carbajala [email protected];

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Josue Isaac Juarez-Hernandeza [email protected]; Rosario Erea TorresGomeza [email protected]; Alberto Pina-Escobedoa [email protected];

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Otoniel Mayaa [email protected]; Carlos Hoyo-Vadillob [email protected]; Emma Gloria Ramos-Ramírezc [email protected]; Juan Alfredo Salazar-

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Montoyac [email protected]; Jaime Garcia-Menaa* [email protected] a

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Departamento de Genética y Biología Molecular, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional. Av IPN 2508 Col Zacatenco, Ciudad de México, 07360.

b

Departamento de Biotecnología y Bioingeniería, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional. Av IPN 2508 Col Zacatenco, Ciudad de México, 07360.

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c

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Departamento de Farmacología, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional. Av IPN 2508 Col Zacatenco, Ciudad de México, 07360.

#

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These two authors contributed equally to this work.

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*Corresponding Author: Jaime García-Mena. Departamento de Genética y Biología

Molecular, Cinvestav, Av Instituto Politécnico Nacional 2508, Ciudad de México, 07360, Mexico. [email protected] Phone number - 57473800, extension – 5328

ACCEPTED MANUSCRIPT Abstract

Cheese is a live food whose preparation involves procedures and microbial communities playing an important role for the final product. We characterized the

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bacterial and fungal diversity of seventeen different Mexican cheeses by high-

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throughput DNA sequencing of 16S/18S rDNA libraries. We propose the existence

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of bacterial and fungal core communities, where at genera level, bacteria include

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Streptococcus spp., Lactococcus spp., Lactobacillus spp., Aerococcus spp., and Weisella spp. while at species level, the fungal community includes Galactomyces

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reessii, Scheffersomyces stipitis, Saccharomyces cerevisiae (baker’s yeast), and S. cerevisiae_rm11-1a. In addition to the bacterial and fungal core communities,

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we found members of the cheese microbiota that could be associated to other

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factors of the cheese manufacturing process. Co-occurrence analysis made in this

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work, indicates that bacterial and fungal communities maintain positive and negative interactions which are important to shape the resident microbial

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communities in cheeses. This work is a contribution to the description of the

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microbial diversity found in some Mexican cheeses.

Keywords: Mexican cheeses; cheese microbiota; cheese fungi; cheese yeast; cheese bacteria; high throughput sequencing; co-occurrence analysis.

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Abbreviations QIIME Quantitative Insights Into Microbial Ecology pipeline

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OTUs Operational taxonomic units

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1. Introduction

Cheese is one palatable way of consuming milk proteins whose origins in

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human history are referred to present time Asian Turkey over 7000 years B. C.

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(Salque et al., 2013). Nowadays this dairy product has more than 1000 varieties

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available all over the world, made mostly from cow's milk (McSweeney et al.,

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2004). In addition to the attributes each cheese style obtains from the type of milk and procedure followed for its preparation; the indigenous microbial community of

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bacteria, yeast and molds coming from milk, and other process-related sources

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play an important role in the development of each cheese variety (Montel et al., 2014; Steele et al., 2013). For instance, a recent report on the characterization of

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German milk microbiota using Fourier Transform-Infrared Spectroscopy, reported

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that on average, the raw milk microbiota is composed of 55% gram-negative bacteria, 41% gram-positive bacteria, and 4% yeasts; in this manner the detection

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of unknown species, suggests that a large fraction of unexplored microbiota may

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contribute to the cheese properties (von Neubeck et al., 2015). Being of premium importance to improve cheese properties, it is of interest to characterize the microbial communities involved in its preparation, with the purpose of developing more defined procedures to make cheese. With this interest, novel molecular biology technologies based on DNA polymorphism have been applied to investigate the richness and abundance of microbial communities (Ndoye et al., 2011; Quigley et al., 2011). It is known that in many cheese types,

ACCEPTED MANUSCRIPT the growth of lactic acid bacteria (LAB), is responsible for acidification and precipitation of the milk protein-casein, separating the curds and whey (Fox et al., 2004). Recent published data of twelve French cheeses indicates that in addition to

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lactic acid bacteria, cheese microbiota shows a prevalence of microbial species

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belonging to Psychrobacter, Pseudomonas, Pseudoalteromonas, Halomonas and

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Psychroflexus genera (Dugat-Bony et al., 2016). In addition, fungi such as Geotrichum candidum, Debaryomyces hansenii, Kluyveromyces spp., Yarrowia

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lipolytica, Candida spp., Clavispora lusitania, Cyberlindnera jadinii, Saccharomyces

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cerevisiae and Torulaspora delbrueckii, and secondary microbiota such as Penicillium sp. Trichothecium domesticum, Mucor lanceolatus and M. racemosus

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were also described (Dugat-Bony et al., 2016).

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In the American continent, there are no reports of indigenous cheese consumption, until the arrival of Europeans and their livestock back in the XVI

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century. In this way, the history of cheese production in Mexico goes back to nearly

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over 500 years (Cervantes-Escoto et al., 2013). However, even though this short history, there are more than 40 varieties of cheeses available in Mexico (Villegas

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de Gante & Cervantes-Escoto, 2011). Within these varieties, the most common cheeses are fresh ones; all of them made following recipes from Europe, but adapted to the new world taste (Villegas de Gante, 2003). Nowadays according to the United States Department of Agriculture, Mexico ranked in the 9th position with 1.5% of the cheese world production in 2017 (Dairy: World Markets and Trade, 2017).

ACCEPTED MANUSCRIPT In Mexico, there are distinctive types of cheeses with different texture-flavor, some with extraordinary culinary value such as “Cotija”, “Oaxaca”, “Poro”, “Chihuahua”, among others (Caro et al., 2014). Work on “Cotija” cheese permitted identification of Lactobacillus spp., Leuconostoc spp. and Weisella spp. as

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dominant bacteria (Escobar-Zepeda et al., 2016), and Candida etchellsii, Pichia

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kudriavzevii and Moniliella suaveolens as important yeast for cheese ripening

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(Chombo-Morales et al., 2016). “Oaxaca” style cheese is another interesting example (Caro et al., 2011); unfortunately, in this work the characterization of the

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microbial community composition only addressed lactobacilli strains identified at

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species level by 16S rDNA sequencing (Caro et al., 2013). For the case of “Poro” cheese, an effort to characterize its bacterial diversity by high-throughput DNA

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sequencing, showed Streptococcus thermophilus and Lactobacillus delbrueckii as

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dominant bacteria, selected during the manufacturing process (Aldrete-Tapia et al., 2014). For “Chihuahua” cheese, bacterial characterization based on 16S rDNA

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identified Streptococcus thermophilus, S. macedonicus, Lactococcus lactis,

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Lactobacillus plantarum, and Leuconostoc mesenteroides as abundant species that play a role in this cheese features; however, the presence of yeast was not

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explored (Renye et al., 2011). In addition, there are dairy Mexican products such as “Jocoque”, a type of Lebanese-cheese-yoghurt (Labneh) (Bou Khozam et al., 2012), where no microbiological study has been reported. In this manner, there is a need to develop studies aiming to characterize the bacterial-fungal diversity in Mexican cheeses. Although there is an Official Mexican Standard for cheese making (NOM-243-SSA1-2010), it does not address the importance of microbial composition.

ACCEPTED MANUSCRIPT In this study, we provide information about both bacterial and fungal communities found in representative samples of soft to semi-hard Mexican cheeses, made with pasteurized or raw milk with no addition of starter cultures (Table 1), which were obtained from different production areas in Mexico (Fig. 1).

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The communities were characterized by high-throughput DNA sequencing of 16S

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microbial diversity found in some Mexican cheeses.

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and 18S rDNA libraries. This work is a contribution to the description of the

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2. Materials and methods

2.1 Sample collection

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For each of the seventeen Mexican cheeses, three specimens from different

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manufacturer, same area, same day, and season were collected and transported

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to the laboratory at 4 °C. Mexican cheeses do not have a well-defined rind layer; for every single cheese type, a sample was aseptically taken from the core of each

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of the three collected specimens for analysis (Fig. 1 and Table 1).

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2.2. Chemical composition analyses Moisture was measured by the thermobalance method (NMX-F-428-1982), ash (AOAC 923.03) and protein (AOAC 960.52) by standard methods, and fat by the Gerber-Van Gulik method (NMX-F-100-1984). All determinations were made by triplicate except for fat made by duplicate.

ACCEPTED MANUSCRIPT 2.3. DNA extraction from cheese 0.1 g of each cheese specimen cores were dispersed by vortex in 500 µL of 2.0 % SDS using 0.6 g of 0.45-0.50 mm sterile glass beads (Arthur H. Thomas IPKIK Cat. NO5663 R50). The three dispersions corresponding to each cheese

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type were pooled and microbial genomic DNA was extracted using phenol-

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chloroform method (García-Mena et al., 2016).

2.4. Construction of the 16S and 18S rDNA libraries

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For bacterial 16S rDNA libraries, amplicons of ~552 bp, including V3-V4

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polymorphic regions were amplified using forward primers (positions 340-356), and reverse primers (positions 784-804) of the Escherichia coli 16S rDNA molecule

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rrnB GenBank J01859.1 (Fig. 2a) (Brosius et al., 1978; Ehresmann et al., 1972).

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From this amplicon an average of 209 bases that included only the V3 region were sequenced (Fig. 2b). For fungal 18S rDNA libraries, amplicons of ~383 bp,

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including V5 polymorphic region (Hadziavdic et al., 2014) were amplified using

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forward primers (positions 973-991), and reverse primers (positions 1243-1268) of the Saccharomyces cerevisiae 18S rDNA molecule GenBank Z75578.1 (Fig. 2c)

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(Kurtzman & Robnett, 2003). From this amplicon ~296 bases including the entire V6 polymorphic region were sequenced (Fig. 2c). Forward and reverse primers have been previously reported (Murugesan et al., 2015) (Table S1 and S2). The PCR program for 16S/18S rDNA amplicon was 5 min, 95 °C; 25 cycles (30 s, 94 °C; 30 s at 62 °C; 30 s 72 °C), and 10 min final extension at 72 °C using PCR 2700 Thermocycler (Applied Biosystems).

ACCEPTED MANUSCRIPT 2.5. High throughput DNA sequencing and analysis Amplicons were processed by Ion Torrent semiconductor sequencing, as previously described (Murugesan et al., 2015). We used Ion OneTouchTM 400 Template Kit v2 DL (Life Technologies) and Ion 318 v2 Chips and Ion Torrent PGM

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system. Sequencing data were analyzed using QIIME (Quantitative Insights Into

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Microbial Ecology pipeline, v1.9.0) as previously reported (García-Mena et al.,

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2016). We obtained an average of 72,200 reads per sample for 16S, and an average of 326,637 reads per sample for 18S rDNA libraries. OTUs (Operational

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taxonomic unit) picking were done against SILVA (v132) database for bacteria, and

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SILVA (v108) database for fungi (Yilmaz et al., 2014).

diversity

was

assessed

with

phyloseq-R

package

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Shannon-Wiener

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2.6. Microbial diversity and co-occurrence analyses

(McMurdie et al., 2013). Dissimilarity in bacterial and fungal communities among

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samples was explored using unweighted UniFrac beta-diversity analysis of the

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otu_table.biom files in QIIME pipeline. Hierarchical clustering of bacterial relative abundance among cheeses was made using gplots, Heatplus and vegan R

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packages. Images like heatmaps were plotted using ggplot2 and RcolorBrewer (v1.1-2) packages. Co-occurrence analysis of members of the bacterial and fungal communities was made using CoNet (Co-occurrence Network Inference) tool (Faust & Raes, 2016) in Cytoscape v3.6.1. To avoid false positive results, correction for multiple-testing (p-value), and correction by Benjamini-Hochberg method (qvalue) were made. Correlations were sorted for statistical significance (p < 0.05) and R >0.6.

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3. Results

3.1. Chemical composition of cheeses

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Cheese properties such as moisture, ashes, proteins and fat content were

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measured for all cheeses (Table 2). Among them Jocoque (JOC), showed the

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highest value of moisture (72.7%), while Chihuahua (CHI) cheese had the lowest

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value (37.7%). The ash content was measured and calculated for dry matter, and Doble-Crema (CHP) showed the highest amount of ash (19.7%), and Jocoque

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(JOC) the lowest (2.2%).

Protein content in cheese sample was also measured and the cheese with

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the highest protein content was Doble-Crema (CHP) (49.7%), and the cheese with

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the lowest content was Jocoque (JOC) (22.3%) (Table 2). The fat content was also

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measured and the cheese with the highest fat content was Jocoque (JOC) (59.7%), and the cheese with the lowest fat content was Doble-Crema (CHP)

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(17.0%) (Table 2).

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3.2. Bacterial phyla abundance DNA libraries for bacterial diversity based on the 16S rDNA (Fig. 2A) were prepared by PCR for the seventeen different cheeses. Libraries were highthroughput sequenced and data analyzed as described in Materials and methods. From this analysis, bacterial phyla such as Acidobacteria, Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria were identified. Bacteria from the

ACCEPTED MANUSCRIPT phylum Firmicutes were relatively more abundant in Chihuahua (CHI) (99.4%), Doble-Crema (CHP) (99.3%), Adobera-para-fundir (AP) (99.3%), and Jocoque (JOC) (98.2%) cheeses (Fig. 3A). For the phylum Proteobacteria, Ranchero (RVER) showed a relative abundance of 95.0%, Adobera-de-mesa (AM) showed

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an abundance of 86.7%, Canasta (CAN) showed an abundance of 84.4%, and

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Panela (PA) made with unpasteurized milk an abundance of 45.7% (Fig. 3A). On

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the other hand, the phylum Acidobacteria was most abundant in Oaxaca (OAX) (0.3%) cheese. The Cincho (CIN) cheese made with unpasteurized milk, showed

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the highest abundance of Actinobacteria (0.6%), while Zacatecas (ZAC) had the

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highest relative abundance of Bacteroidetes of 1.5% among all studied cheeses

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(Fig. 3A).

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3.3. Bacterial genera abundance

Bacterial relative abundance was also analyzed at genus level. Thirty

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different bacterial genera were identified (Fig. 3B and Table 3), in which

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Lactococcus and Streptococcus from same phyla (Firmicutes) were highly abundant, followed by Lactobacillus, Marinomonas, Aeromonas, Aerococcus, and

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Pectobacterium. Among these bacteria, Lactococcus was more abundant in Manchego (MAN) (86.1%), followed by Jocoque (JOC) (75.2%), Panela (PP) (57.0%), and Ranchero (RED) (48.7%) cheeses. For other Firmicutes, Adoberapara-fundir (AP) cheese made with pasteurized milk, showed the highest abundance of Streptococcus (77.1%), followed by Oaxaca (OAX) with 70.8%, Adobera-para-fundir (AA) with 68.4%, Cincho (CIN) (60.4%), and Zacatecas (ZAC) (40.3%) cheeses. Lactobacillus (Firmicutes), showed a relative abundance of

ACCEPTED MANUSCRIPT 83.3% in Doble-Crema (CHP) cheese, 50.2% in Chihuahua (CHI), dropping to 16.1% in Zacatecas (ZAC), and 5.7% in Adobera-para-fundir (AP) cheeses (Fig. 3B and Table 3). In case of Aerococcus, another genus of Firmicutes bacteria, Cotija (COT) cheese presented highest abundance (27.8%), followed by Adobera-

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de-mesa (AM) with 2.9%.

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For the case of Proteobacteria, the genus Marinomonas was abundant in

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Adobera-de-mesa (AM) cheese (82.5%), and Ranchero (RVER) cheese (79.2%), Aeromonas was another abundant genus in Panela (PA) with 41.2%, Cotija (COT)

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with 24.7%, followed by Ranchero (RED), Ranchero (RVER), Adobera-para-fundir

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(AA), and Jocoque (JOC) with less than 6.0%. Other genera as Serratia (16.1%), Pantoea (9.2%) were abundant in Canasta (CAN) cheese. The genus

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Peptobacterium was significantly abundant in Canasta (CAN) cheese (34.0%), but

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the presence of this genus dropped down severely in other cheeses like Cincho (CIN) to 1.9%. Panela cheese (PP) showed the highest abundance of Enterobacter

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(4.5%), followed by Cincho (CIN) (4.2%) cheese. Finally, the genera Leuconostoc,

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and Weissella were among other moderately abundant bacteria in the Mexican cheeses studied in this work (Fig. 3B and Table 3).

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Sequencing data were also analyzed to show the similarity in the abundance of top-fifteen selected bacterial genera in cheeses Supplementary Material of the Appendix A (Fig. S2). From this analysis, the hierarchical clustering of relative abundance of bacterial profiles (vertical axis) showed that bacterial profiles are not the same among different cheeses, and some cheeses are grouped according to the bacterial relative abundance. This analysis shows that Canasta (CAN) cheese microbiota profile was completely distinct of all other

ACCEPTED MANUSCRIPT cheeses in this work. Moreover, hierarchical clustering among the selected bacteria (horizontal axis) also shows that the most abundant bacterial genera were Streptococcus, Lactococcus, Lactobacillus, and Marinomonas. The lactic acid bacterium Streptococcus was more abundant especially in Oaxaca (OAX), Cincho

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(CIN), Ranchero (RED), Chihuahua (CHI), Adobera-de-mesa (AA), and Zacatecas

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(ZAC) cheeses. On the other side, Lactococcus was more abundant particularly in

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Jocoque (JOC), Ranchero (RED), Manchego (MAN), and Chihuahua (CHI) cheeses; Lactobacillus was more abundant in Doble-Crema (CHP) and Chihuahua

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3.4. Fungal Genera abundance

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(AM), and Ranchero (RVER) (Fig. S2).

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(CHI) cheeses. In addition, Marinomonas was more abundant in Adobera-de-mesa

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The 18S rDNA libraries corresponding to the seventeen different Mexican cheeses (Fig. 2B) were also high-throughput sequenced and data analyzed as

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described in Materials and methods. From this analysis, we identified members of

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the phyla Ascomycota and Basidiomycota, and fungal relative abundance was also analyzed at genus level. Sixteen different fungal genera were identified (Fig. 5A), in

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which Galactomyces, Saccharomyces and Scheffersomyces were more abundant among all cheeses, followed by Yarrowia, and members of the subkingdom Dikarya. Among these fungi, Galactomyces was more abundant in Zacatecas (ZAC) cheese (95.4%), and Ranchero (RVER) cheese (91.8%), but the abundance dropped in Jocoque (JOC) to 68.2%, Panela (PA) to 49.6% and 48.9% in Ranchero (RED) cheese (Fig. 5A and Table 4). In the case of Saccharomyces, Cincho (CIN) cheese showed the highest abundance (87.2%) followed by Doble-

ACCEPTED MANUSCRIPT Crema (CHP) cheese with 79.4%, Adobera-de-mesa with 41.7% and Ranchero (RED) with 38.9% (Fig. 5A and Table 4). On the other hand, Scheffersomyces presented the highest abundance in Cotija (COT) with 82.4%, Panela (PP) with 74.0%, Oaxaca (OAX) with 67.3% and

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Adobera-para-fundir (AA) with 63.6%. The subkingdom Dikarya was more

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abundant in Panela (PA) cheese (30.1%) followed by Panela (PP) with 16.7% (Fig.

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4a) (Table 4). Yarrowia was more abundant in Adobera-para-fundir (AA) (16.3%) than in all other cheeses. In general, the genus Candida, Hanseniaspora,

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Kazachstania, Pichia, and Vanderwaltozyma were among the least abundant fungi

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3.5. Fungal species abundance

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found in cheeses used in this study (Fig. 5A and Table 4).

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Fungal abundance was analyzed at species level (Fig. 5B and Table 5). Twentyeight different fungal species were identified, among them Galactomyces reessii,

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Scheffersomyces stipitis, Saccharomyces cerevisiae (baker’s yeast), and S.

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cerevisiae rm11-1a were the most abundant. G. reessii was especially more abundant in Zacatecas (ZAC) (95.4%), Ranchero (RVER) (91.8%), Jocoque (JOC)

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(68.2%) and Panela (PA) (49.6%) cheeses. Scheffersomyces stipitis was highly abundant in Cotija (COT) cheese (82.4%), Panela (PP) (74.0%), Oaxaca (OAX) (67.3%), and Adobera-para-fundir (AA) (63.6%) cheeses. In case of S. cerevisiae (baker’s yeast), Cincho (CIN) cheese showed the highest abundance (66.0%); followed by Doble-Crema (CHP) (29.7%), Adobera-para-fundir (AA) (17.5%), and Jocoque (JOC) (16.0%) cheeses. On the other hand, S. cerevisiae rm11-1a was present more abundantly in Doble-Crema (CHP) (49.7%), Adobera-de-Mesa (AM)

ACCEPTED MANUSCRIPT (33.6%), Ranchero (RED) (29.7%) and Cincho (CIN) (21.2%) cheeses. Yarrowia lipolytica was more abundant in Adobera-para-fundir (AA) (16.3%) than in other cheeses. Candida naeodendra, Hanseniaspora osmophila, Kazachstania aquatica, Vanderwaltozyma polyspora and Pichia dryadoides were the other least abundant

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fungi found in this study (Fig. 5B and Table 5).

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Data were also analyzed to show the similarity in abundance of selected

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fungi in relation to each cheese Supplementary Material of the Appendix A (Fig. S3). From this analysis, the hierarchical clustering (vertical axis) showed that

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fungal profiles are not the same among different cheeses, and some cheeses are

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grouped according to the fungal relative abundance. Moreover, hierarchical clustering among the selected fungi (horizontal axis) also showed that

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Galactomyces reessii was the most abundant fungi in Panela (PA), followed by

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Zacatecas (ZAC) cheese; after them, Ranchero (RVER), Jocoque (JOC), Asadero (ASA) and Ranchero (RED) cheeses showed a high abundance. Scheffersomyces

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stipitis was more abundantly present in Adobera-de-mesa (AM), and Asadero

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(ASA), followed by Oaxaca (OAX) and Panela (PP) cheeses. The same analysis showed that Saccharomyces cerevisiae (baker’s yeast) was more abundant in

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Cincho (CIN) cheese, followed by Doble-Crema (CHP) and Jocoque (JOC). Finally, S. cerevisiae rm11-1a was more abundant in Adobera-de-Mesa (AM), followed by Doble-Crema (CHP), Ranchero (RED) and Cincho (CIN) (Fig. S3).

3.6. Dissimilarity and co-occurrence analyses of bacterial and fungal communities

ACCEPTED MANUSCRIPT The beta-diversity analysis of bacterial and fungal communities among cheese samples using weighted, unweighted UniFrac, or Bray-Curtis, with different metadata as geographical origin, type of cheese, type of milk, and chemical composition did not show any significant dissimilarity. However, when the beta-

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diversity was explored using unweighted UniFrac analysis alone without metadata,

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the beta-diversity of the bacterial and fungal communities clustered apart the

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cheeses into two groups, where the microbial communities of 9 out of 17 cheeses MAN, PA, RED, OAX, COT, RVER, AA, ZAC and CIN were clustered together

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(Fig. 5A and Fig. 5B); these results suggested a potential co-occurrence of some of

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the members. We performed a co-occurrence analysis of the bacterial and fungal communities in all the 17 cheeses as described in Material and methods. We found

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an interesting network including 73 statistically significant bacterial and fungal co-

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presence and mutual exclusion interactions (Fig. 6, Table 6). The same analysis also showed the existence of 15 additional networks. A figure and table containing

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all the data are included in the Supplementary Material of the Appendix A (Fig. S4,

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Table S3), and the Appendices B and C.

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4. Discussion

In Mexico, there are more than 40 varieties of artisanal cheeses; one important characteristic among them is that they are commonly not aged in comparison to cheeses from other part of the world (González-Córdova, et al., 2016). This cheese diversity is due to the specific preparation, as well as other

ACCEPTED MANUSCRIPT factors added during the manufacturing process, such as starter cultures, raw ingredients like milk, and very importantly, the microbial community acquired during the preparation, that deserves to be studied (Button & Dutton, 2012). In this work, we characterized the bacterial and fungal communities in a sample of several

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different Mexican cheeses by 16S/18S rDNA fingerprinting. We found each cheese

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has a particular microbial community conferring to it particular palatable and

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chemical attributes Supplementary Material of the Appendix A (Fig. S1). We studied a selected sample of soft to semi-hard cheeses, made with

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pasteurized or raw milk (Table 1), obtained from different production areas in

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Mexico (Fig. 1). A basic chemical study was made, measuring moisture, ashes, proteins and fat content. Values ranged according to the curd. Moisture ranged

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from 37–72%, the ash content in the dry matter was 5–20%, protein ranged from

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25–50%, while the fat values were from 20–60% (Table 2). We did not find a relationship between these basic values and bacterial or fungal diversities (Table 3

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and Table 5).

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The high throughput sequencing of 16S rDNA libraries showed that bacterial communities are different among cheeses. In general, Firmicutes are the most

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abundant bacteria phylum, followed by Proteobacteria (Fig. 3A). At genera level, the Bacterial Core Community (BCC) includes Streptococcus, Lactococcus, and Lactobacillus (Fig. 3B). Other abundant genera in cheeses are the Firmicutes Aerococcus, and Weisella and the Proteobacteria, Aeromonas, and Marinomonas (Supplementary Material of the Appendix A (Fig. S2) and Table 3). These results agree with published work in other cheeses (Ceugniez et al., 2017; Dolci et al., 2014; Guidone et al., 2016)

ACCEPTED MANUSCRIPT In addition to the BCC in cheese, abundant bacterial genera are Marinomonas and Aeromonas in Ranchero (RVER), and Pectobacterium and Serratia in Canasta (CAN) (Table 3). The origin of these bacteria in cheese may be diverse.

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The Ranchero (RVER) cheese comes from a coastal area in Mexico (Fig.

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1), where the manufacturing process use raw milk which might contain

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proteobacteria and thus be one source of the highly abundant genera Marinomonas (79.2%) and Aeromonas (4.6%) in this type of cheese (Table 3).

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Marinomonas and Aeromonas are coastal sea proteobacteria, which have been

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identified in cheeses like Pico cheese from Portugal (Riquelme et al., 2015); these two Proteobacteria are common members of the cheese rind microbial

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communities in several soft, semi-hard and hard European cheeses (Irlinger et al.,

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2015). We collected another Ranchero (RED) cheese, made in the central part of Mexico at 2,452 m over sea level (Fig. 1). In this specimen, the microbial diversity

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reflects three genera members of the BCC including Lactococcus, Streptococcus,

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and Lactobacillus. Although this cheese was made also with raw milk and presented similar chemical properties like Ranchero (RVER) cheese (Table 2), the

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bacterial community is different from the one made close to the sea. This is an example, of how the manufacturing environment or the source of the raw milk may influence the bacterial diversity, and why it is important to characterize them. In Canasta (CAN) cheese, the manufacturing process including a wicker basket to shape the curd, may select a peculiar bacterial community, where its genera members (Pectobacterium, Serratia, Yersinia and Pantoea), account for 74.5% of abundance, being the BCC less than 5.0% of the community (Table 3).

ACCEPTED MANUSCRIPT We should mention that Pectobacterium (Motyka et al., 2017), Serratia (Mahlen, 2011), Yersinia (Schiemann, 1978), and Pantoea (Mardaneh & Dallal, 2013), are genera with members not commonly reported as part of the cheese microbiota. On regard of fungi, the high throughput sequencing of 18S rDNA libraries,

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showed that fungal communities are also different and among cheeses. The more

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abundant are from the phylum Ascomycota, and other members of the subkingdom

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Dikarya (Fig. 5A and Fig. 5B). Based on our results we propose the existence of a Fungal Core Community (FCC) including members of the species Galactomyces

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reessii, Scheffersomyces stipitis, Saccharomyces cerevisiae (baker’s yeast), and

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S. cerevisiae_rm11-1a (Fig. 6 and Table 5). Similar results have been reported for French cheeses (Dugat-Bony et al., 2016).

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In addition to the FCC members, some cheeses like Adobera-para-fundir

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(AA), Adobera-de-mesa (AM), Cotija (COT), Panela (PP), Panela (PA), DobleCrema (CHP), Cincho (CIN), and Asadero (ASA) presented peculiar fungal

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communities. Adobera-para-fundir (AA) showed as more abundant yeast

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Scheffersomyces stipitis (63.6%), a member of the FCC. We also found the presence of Yarrowia lipolytica (16.3%) and Candida naeodendra (2.7%) besides

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the FCC members. Y. lipolytica is an abundant yeast in ripened surfaces of Danish cheese, producing different flavor compounds (Sørensen et al., 2011), while some strains of S. stipitis, are reported in ethanol production (Puseenam et al., 2015). Adobera-de-mesa (AM) has in addition to the FCC, an evident presence of Candida naeodendra, a potential killer yeast abundant in fermented foods such as miso, soy sauce and salted vegetables (Suzuki et al., 1989).

ACCEPTED MANUSCRIPT The Cotija (COT) bacterial community has been characterized (EscobarZepeda et al., 2016); however, the study spared the fungal community. In our study, in addition to the FCC leaded by S. stipitis (82.4%), we detected a significant abundance of Fusarium oxysporum f. sp. lycopersici 4286 (3.1%) a plant pathogen

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(Nirmaladevi et al., 2016) (Table 5). In Mexico, tomato crops from the Jalisco State,

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in the area where this cheese is made, are severely affected by this fungus.

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Three semi-soft cheeses like Panela (PP), Panela (PA), and Asadero (ASA) had the FCC; however, they also showed the presence of members of the

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subkingdom Dikarya in Panela (PP) (16.6%), Panela (PA) (30.1%), and Asadero

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(ASA) (1.9%) (Table 5). Dikarya are fungi from the phylum Ascomycota or Basidiomycota, the last includes members that may produce basidiocarps (Fig. 5A

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and Fig. 5B). Doble-Crema (CHP) another semi-soft cheese has abundant

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Saccharomyces cerevisiae (79.4%) (Fig. 5B and Fig. 6); however, it also has two specific yeasts, Hanseniaspora osmophila, and Kazachstania aquatic. The fungi H.

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osmophila is reported as beneficial for fermented foods (Bourdichon et al., 2012);

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while the genus Kazachstania spp. is reported for ripening of Camembert-type cheeses (Mei et al., 2014).

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Finally, Cincho (CIN) had a combined FCC of S. cerevisiae (baker’s yeast); S. cerevisiae_rm11-1a and S. stipitis of 89.1%, and low abundance of Candida sagamina (1.8%). This yeast has been reported associated to beetles (Suh & Blackwell, 2005), but it might have some unsuspected roles in this cheese properties. The beta-diversity analysis of the bacterial and fungal communities clustered apart the cheeses into two groups, as was observed for the MAN, PA,

ACCEPTED MANUSCRIPT RED, OAX, COT, RVER, AA, ZAC and CIN (Fig. 5A and Fig. 5B), suggesting a potential co-occurrence of some of the microbial members. Interestingly, the cooccurrence analysis of the bacterial and fungal communities in all the 17 cheeses disclosed 16 networks. One interesting network includes 73 statistically significant

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bacterial and fungal co-presence and mutual exclusion interactions (Fig. 6, Table

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6). For instance, Firmicutes like Lactococcus (B05, B06, B07, B08), a genus

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member of the proposed Bacterial Core Community, maintain positive copresence interactions among them, but negative mutual exclusion interaction with an

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uncultured fungus (F02) detected in this study. Paenibacillus (B04), another

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Firmicutes, maintain copresence interaction with Bacillus cereus (B01), Clostridium (B02), and Pseudomonas (B03); while it has mutual exclusion interaction with

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uncultured fungi (F02, F03), Candida_sp._bg02-5-30-009a-1 (F04), and Candida

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solani (F05). It is important to mention that based on this analysis Bacillus cereus (B01), Clostridium (B02), and Pseudomonas (B03) maintain a positive co-presence

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interaction among them (Fig. 6, Table 6). A strain of Paenibacillus sp. along with

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Bacillus cereus, and Clostridium sp. have been reported as part of the microbial dynamics during the shelf-life of industrial Ricotta cheese (Sattin et al., 2016).

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The results of our analysis also show that in general, members of the fungal community maintain positive co-presence interactions among them and mutual exclusion interactions with bacteria. Scheffersomyces stipitis (F08), a member of our proposed Fungal Core Community has only one positive interaction with Millerozyma farinosa (F07), however our analysis shows that less abundant fungi like Candida drimydis (F06) maintain nine, while Candida_sp._nrrl_y-7574 (F11) and Millerozyma farinosa (F07) maintain eight positive copresence interactions

ACCEPTED MANUSCRIPT with other members (Fig. 6 and Table 5). The 15 additional networks illustrate seven positive co-occurrence interaction among bacteria and eight among members of the fungal community as is shown in the Supplementary Material of the Appendix A

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(Fig. S4, Table S3), and the Appendices B and C.

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5. Conclusions

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Our suggestion for bacterial and fungal core communities in Mexican cheeses is supported by reports of high abundance of bacteria (Saxer et al., 2013)

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and yeast (Magallon et al., 2011) identified in this work and in other cheeses. We concluded that microbial communities in Mexican cheeses, is wide and diverse for

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both bacteria and fungi. In our study, 14 out of 17 cheeses are handmade in

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traditional ways with not addition of starter cultures, however, we believe cheese

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microbial communities are influenced by local factors like climate, elevation, milk microbiota, handling, and processing environment. These factors could be a

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source of “in house microbiota” which influences cheese properties and could make them unique. Co-occurrence analysis made in this work, indicates that

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bacterial and fungal communities maintain positive and negative interactions which are important to shape the resident microbial communities in cheeses. There is still more work to be done, but this study adds information for comparative analysis of different Mexican cheeses in terms of the microbial diversity, and this information is important to understand the cheese properties.

ACCEPTED MANUSCRIPT Data availability

The datasets (raw sequences) generated and analyzed during this study has been submitted to NCBI Sequence Read Archive (SRA) repository with

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accession number SRP072467 for bacteria (16s rDNA) and SRP072514 for fungi

and

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https://www.ncbi.nlm.nih.gov/sra/?term=SRP072467,

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(18S rDNA), and can be access through following links: for Bacteria for

fungi

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https://www.ncbi.nlm.nih.gov/sra/?term=SRP072514

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Acknowledgements

This research was funded by Cinvestav; CONACyT 163235 INFR-2011-01; and

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FONSEC SS/IMSS/ISSSTE-CONACYT-233361 granted to JGM. We thank a

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Postdoctoral Fellowship from FONSEC SS/IMSS/ISSSTE-CONACYT-233361 granted to SM, and CONACyT Doctoral Fellowships granted to OM (346907), and

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KN (589896). We thank the help of M. en C. Loan Edel Villalobos-Flores for

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technical assistance on co-occurrence analysis; IBQ. María Dolores Díaz Cervantes and Rodrigo García-Gutiérrez for technical support and Ms. Miriam Odet Escobar Matamoros for administrative assistance.

Declarations of interest: none.

Research involving Human Participants and/or Animals

ACCEPTED MANUSCRIPT This work does not contain any studies with human participants or animals.

Informed consent

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Does not apply for this work.

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Author contributions

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Author contributions: JGM, SM, KN performed literature search, conceived and designed the study. MPRM, JIJH, RETG, JASM collected data and conducted the

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experiments. APE, performed high-throughput DNA sequencing. SM, OM, KN,

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performed data analyses. JGM, CHV, EGRR, JASM, participated in study design and interpretation. JGM, ACC, SM, KN wrote the manuscript with critical review

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input from all the authors.

Appendix A. Supplementary data

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Supplementary data to this article can be found online at...

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Appendix B. Supplementary data Supplementary data to this article can be found online at...

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Appendix C. Supplementary data Supplementary data to this article can be found online at...

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Figure legends

Fig. 1. Map of the origin of cheese samples in the Mexican republic. The figure

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indicates the states where the cheese samples were collected according to the data shown in Table 1. Cheeses are identified as AP, Adobera-para-fundir; AA,

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Adobera-para-fundir; AM, Adobera-de-mesa; COT, Cotija; PP, Panela; PA, Panela;

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JOC, Jocoque; CHP, Doble-Crema; RED, Ranchero; RVER, Ranchero; ZAC,

Asadero;

MAN,

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Zacatecas; CHI, Chihuahua; CIN, Cincho, OAX, Oaxaca; CAN, Canasta; ASA, Manchego.

Small

earth

image

was

adapted

from

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https://commons.wikimedia.org/w/index.php?curid=16381149.

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Fig. 2. Map of the 16S and 18S rDNA genes and primers. a Representation of Brosius 1,541 bp rrnB 16S ribosomal gene of E. coli. The primer V3-341F indicates the complementary sequence for the forward primers (positions 340-356), and the reverse V4-805R primer (position 784-804) of the Escherichia coli 16S rDNA molecule rrnB GenBank J01859.1. b Representation of the 552 bp PCR amplicon obtained from the rrnB GenBank J01859.1 molecule, showing the details of the

ACCEPTED MANUSCRIPT forward and reverse primers used for ion semiconductor sequencing. The solid black color broken arrow indicates the approximately 209 bases sequenced from the forward primer in our work. c Representation of 18S ribosomal gene of Saccharomyces cerevisiae (baker’s yeast). The primer 18S-F indicates the

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complementary sequence for the forward primers (position 973-991), and reverse

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18S-200 R (positions 1243-1268) of the Saccharomyces cerevisiae 18S rDNA

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molecule GenBank Z75578.1. Primer series used for 16S/18S rDNA based highthroughput sequencing are described in Materials and methods section (Online

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Resource Table OR1, OR2). Solid arrows indicate complementary regions for

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primers; larger grey color filled arrows from V1 to V9, indicate the polymorphic variable sequences in the molecules. V6 region is not annotated in the S.

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cerevisiae 18S rDNA molecule, since it is not sufficiently polymorphic (see

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Materials and methods).

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Fig. 3. Relative abundance of bacteria in Mexican cheeses. The figure shows a

different

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graphic display of the more abundant phyla and genera observed in the 17 Mexican

cheeses

studied,

determined

by high-throughput

DNA

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sequencing of V3-V4 16S rDNA libraries prepared from extracted genomic DNA from cheeses as described in Materials and methods. Y-axis shows % of relative abundance; X-axis indicates the abundance for a cheese; each taxonomic category is shown by a different color; a phylum, b genus. Cheeses are identified as AP, Adobera-para-fundir; AA, Adobera-para-fundir; AM, Adobera-de-mesa; COT, Cotija; PP, Panela; PA, Panela; JOC, Jocoque; CHP, Doble-Crema; RED,

ACCEPTED MANUSCRIPT Ranchero; RVER, Ranchero; ZAC, Zacatecas; CHI, Chihuahua; CIN, Cincho, OAX, Oaxaca; CAN, Canasta; ASA, Asadero; MAN, Manchego (Table 1).

Fig. 4. Relative abundance of yeast in Mexican cheeses. The figure shows a

Mexican

cheeses

studied,

determined

by high-throughput

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different

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graphic display of the more abundant genera and species observed in the 17 DNA

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sequencing of V5 18S rDNA libraries prepared from extracted genomic DNA from cheeses as described in Materials and methods. Y-axis shows % of relative

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abundance; X-axis indicates the abundance for a cheese; each taxonomic

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category is shown by a different color; a genus, b species. Cheeses are identified as AP, Adobera-para-fundir; AA, Adobera-para-fundir; AM, Adobera-de-mesa;

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COT, Cotija; PP, Panela; PA, Panela; JOC, Jocoque; CHP, Doble-Crema; RED,

ED

Ranchero; RVER, Ranchero; ZAC, Zacatecas; CHI, Chihuahua; CIN, Cincho,

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OAX, Oaxaca; CAN, Canasta; ASA, Asadero; MAN, Manchego (Table 1).

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Fig. 5. Characterization of beta-diversity in Mexican cheeses. The cheese microbiota beta diversity for bacterial (A) and fungal (B) communities, was

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calculated by dissimilarity metrics using OTU tables and Unweighted UniFrac analyses. The analysis shows the dissimilarity among the different cheeses as percentage of total variability in different axes. Three-dimensional scatter plots were generated using principal coordinates analysis (PCoA). Tags beside the green and red circles in the graphics identify cheeses as AP, Adobera-para-fundir; AA, Adobera-para-fundir; AM, Adobera-de-mesa; COT, Cotija; PP, Panela; PA, Panela; JOC, Jocoque; CHP, Doble-Crema; RED, Ranchero; RVER, Ranchero;

ACCEPTED MANUSCRIPT ZAC, Zacatecas; CHI, Chihuahua; CIN, Cincho, OAX, Oaxaca; CAN, Canasta; ASA, Asadero; MAN, Manchego (Table 1).

Fig. 6. Co-occurrence analysis of the bacterial and fungal communities of the

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studied cheeses. The figure shows selected copresence (green lines) and mutual

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exclusion (red lines) interactions between bacterial (orange color ovals) and fungal

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(grey color ovals) OUT nodes. Analysis was performed using otu_table.biom file using CoNet tool in Cytoscape (v3.6.1) plugin as described in Material and

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methods. Each node indicates the number of OTUs belonging to their taxonomic

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group. Edges (lines) connecting two nodes represent significant correlations (p<0.05; q<0.05). A selected network with interactions among bacterial and fungal

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OTUs is shown here (Table 6). More details of the interactions including the whole

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set of networks are shown in the Supplementary Material of the Appendix A (Fig. S4, Table S3), Appendix B, and Appendix C. Labels inside figures indicate the

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bacterial and fungal taxa as follows: B01, KF625179.1.1776 Bacillus_cereus; B02,

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AF018036.1.1512 Clostridium sp.; B03, AM491464.1.1523 Pseudomonas sp.; B04, AB428571.98.1656 Paenibacillus sp.; B05, OTU10127 Lactococcus sp.; B06,

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AM944736.1.1429 Lactococcus sp.; B07, BCVN01000061.3283.4819 Lactococcus sp; B08, OTU10873 Lactococcus sp.; F01, 41135 Stenamoeba limacine; F02, 100023

Uncultured

fungi;

F03,

14916

Uncultured

fungi;

F04,

87287

Candida_sp._bg02-5-30-009a-1; F05, 7260 Candida solani; F06, 101043 Candida drimydis; F07, 71176 Millerozyma farinosa; F08, 96648 Scheffersomyces stipitis; F09, 71004 Pachysolen_tannophilus; F10, 105830 Candida_lassenensis; F11, 109417 Candida_sp._nrrl_y-7574; F12, 50314 Ambrosiozyma_cicatricosa; F13,

ACCEPTED MANUSCRIPT 46395 Candida_kashinagacola; F14, 134 Williopsis_salicorniae; F15, 99356 Saccharomycopsis_vini;

F16,

14030

Phaeosphaeria_nodorum_sn15;

F18,

Myxozyma_nipponensis;

81147

F22,

99621

106439

Pichia_alni;

Williopsis_pratensis; Candida_quercitrusa;

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PT

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M

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Candida_sp._bcmu_bx01.

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F17, F19,

4269 94711

F21,

112792

F23,

39901

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Pichia_dryadoides;

F20,

Debaryomyces_sp;

ACCEPTED MANUSCRIPT Table 1 Origin of studied Mexican cheeses. &

Doble-Crema (CHP) Ranchero (RED) Ranchero (RVER) Zacatecas (ZAC) Chihuahua (CHI) Cincho (CIN) Oaxaca (OAX) Canasta (CAN) Asadero (ASA) Manchego (MAN)

soft

19°52′N 103°09′W

Tepatitlán, Jalisco State. Zapotlanejo, Jalisco State. Guadalajara, Jalisco State

20°40′00.17″N 102°44′00.23″W 20°37′22″N 103°4′8″W 20°40′N 103°21′W

soft

Pijijiapan, Chiapas State

15°41′N 93°13′W

soft

Jilotepec, Estado-deMéxico State

soft

Tempoal, Veracruz State.

semihard semisoft semihard semisoft

Tequisquiapan, Querétaro State. Ciudad Cuauhtémoc, Chihuahua State.

19°57′07″N 99°31′58″W 21°31′0″N 98°23′0″W 20.5206°N 99.8958°W 28°24′18″N 106°52′00″W

Veracruz State.

19°26′N 96°23′W

soft semisoft semihard

Tulancingo, Hidalgo State Gómez Palacio, Durango State San-Juan-del-Río, Querétaro State. San-Juan-del-Río, Querétaro State.

20°5′0″N 98°22′0″W 25°33′40″N 103°29′54″W 20°23′N 99°59′W 20°23′N 99°59′W

humid subtropical climate “Cfa” humid subtropical climate “Cfa” humid subtropical climate “Cfa” mediterranean climate “Csa” humid subtropical climate “Cfa” humid subtropical climate “Cfa” humid subtropical climate “Cfa” tropical savanna climate “Aw” oceanic subtropical highland climate “Cwb” tropical savanna climate “Aw” tropical and subtropical steppe climate “BSk” tropical and subtropical steppe climate “BSk” tropical savanna climate “Aw” marine west coast climate “Cfb” tropical and subtropical desert climate “Bwh” oceanic subtropical highland climate “Cwb” oceanic subtropical highland climate “Cwb”

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19°55′N 102°01′W

*Climate

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Jocoque (JOC)

soft

San-Miguel-el-Alto, Jalisco State. Manzanilla-de-la-Paz, Jalisco State Concepción-de-Buenos Aires, Jalisco State.

20°40′00.17″N 102°44′00.23″W 21°1′25″N 102°24′21″W

Elevation meters(fe et) 1,820 (5,970) 1,850 (6,069) 2,063 (6,768) 1,779 (5,837) 1,820 (5,971) 1,527 (5,010) 1,545 (5,069) 47 (154) 2,456 (8,058) 59 (194) 1,877 (6,158) 2,055 (6,742) 291 (955) 2,154 (7,067) 1,123 (3,684) 1,920 (6,299) 1,920 (6,299)

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Panela (PA)

soft

Tepatitlán, Jalisco State.

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Panela (PP)

semihard semihard semihard semihard

Coordinates

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Cotija (COT)

P d R w R w R w P d R w R w R w R w R w R w P d R w R w R w R w R w

Place of origin

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Adobera-parafundir (AP) Adobera-parafundir (AA) Adobera-demesa (AM)

Type

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Mi lk

Name

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Pd, cow milk was subjected to pasteurization before cheese making; Rw, raw cow milk was not pasteurized before cheese making. Type, indicates the curd texture. &http://elevation.maplogs.com/; *Köppen climate classification; Source of climate data: https://www.weatherbase.com/weather/state.php3?c=MX&name=Mexico; To see the Köppen climate classification; http://hanschen.org/koppen/#home, Hierarchy are: “Cf” Mild temperate, fully humid; “Cs” Mild temperate with dry summer; “Aw” Tropical savannah with dry winter; “Cw” Mild temperate with dry winter; “BS” Steppe (semi-arid); “BW” Desert (arid); “a” Hot summer; “b” Warm summer; “k” Cold arid; “h” Hot arid.

ACCEPTED MANUSCRIPT Table 2 Chemical composition of studied Mexican cheeses. Proteins in dry matter (%)

Fat in dry matter (%)*

39.24 ±0.48

5.83 ±0.03

34.81 ±0.69

47.72

42.44 ±0.37

5.77 ±0.07

37.58 ±0.60

40.08

44.28 ±0.37

8.83 ±0.07

39.12 ±0.67

38.86

14.75 ±0.19

35.99 ±0.29

4.42 ±0.18

25.80 ±0.64

46.33

5.57 ±0.04

35.10 ±0.40

39.80

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2.20 ±0.22

66.63 ±0.28

37.15

22.28 ±2.74

59.73

49.72 ±1.44

16.96

37.40 ±1.07

43.51

34.43 ±0.90

40.83

29.14 ±0.72

45.56

5.59 ±0.45

32.95 ±1.19

41.03

8.63 ±0.66

38.33 ±2.11

44.98

4.94 ±0.07

35.53 ±1.52

44.98

6.08 ±0.07

32.25 ±1.15

44.25

5.82 ±0.15

31.46 ±1.77

30.24

6.13 ±0.07

38.96 ±0.60

39.24

5.41 ±0.19

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10.64 ±0.04

AN

19.67 ±0.17

ED

5.85 ±0.15

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45.99 ±0.26 50.65 ±0.08 44.58 ±0.25 37.70 ±0.17 42.06 ±0.84 44.93 ±0.54 44.41 ±0.09 46.89 ±0.60 39.96 ±0.54

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46.09 ±0.28 43.92 ±0.32 50.13 ±0.35 72.71 ±0.11

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Ashes in dry matter (%)

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Adoberapara-fundir (AP) Adoberapara-fundir (AA) Adoberade-mesa (AM) Cotija (COT) Panela (PP) Panela (PA) Jocoque (JOC) DobleCrema (CHP) Ranchero (RED) Ranchero (RVER) Zacatecas (ZAC) Chihuahua (CHI) Cincho (CIN) Oaxaca (OAX) Canasta (CAN) Asadero (ASA) Manchego (MAN)

Moisture (%)

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Name

Note: Mean values and ±standard deviations of three independent measurements on different cheese samples. *% Fat content, was made by duplicate and only the average is reported.

ACCEPTED MANUSCRIPT

Genus (%) Lactobacillus (5.7) Lactobacillus (5.2) Aerococcus (2.9)

Clostridium (1.4) Aeromonas (1.6) Enterococcus (1.6)

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Table 3 Most abundant bacterial genera in cheese. SName W Streptococcus Lactococcus Adobera-para- 1.7 (77.1) (13.8) fundir (AP) 3 Streptococcus Lactococcus Adobera-para- 3.3 (68.4) (21.0) fundir (AA) 6 Marinomonas Lactococcus Adobera-de1.6 (82.5) (5.1) mesa (AM) 6

Other s (1.8) Other s (3.6) Other s (7.7) Other s (14.8) Other s (14.1) Other s (7.7) Other s (2.2) Other s (1.3) Other s (6.5) Other s (9.4) Other s (10.6) Other s (1.6) Other s (20.2)

Cotija (COT)

3.0 2

Aerococcus (27.8)

Aeromonas (24.7)

Weissella (23.6)

Panela (PP)

2.7 6

Lactococcus (57.0)

Streptococcu s (19.7)

Lactobacillus (4.6)

Enterobacter (4.5)

Aeromonas (41.2) Lactococcus (75.2) Lactobacillus (83.3) Lactococcus (48.7) Marinomonas (79.2)

Lactococcus (28.8) Streptococcu s (17.7) Streptococcu s (7.8) Streptococcu s (34.5) Aeromonas (4.6)

Streptococcu s (19.3) Lactobacillus (3.9) Weissella (5.0) Aeromonas (6.07)

Enterococcus (2.8)

Doble-Crema (CHP) Ranchero (RED) Ranchero (RVER)

2.8 7 2.2 9 2.7 9 2.9 6 2.2 6

Zacatecas(ZA C)

2.9 1

Streptococcus (40.3)

Lactococcus (31.6)

Lactobacillus (16.1)

Lachnospiraceae (1.2)

Chihuahua (CHI)

2.2 1

Lactobacillus (50.2)

Streptococcu s (24.5)

Lactococcus (23.4)

Weissella (0.1)

Cincho (CIN)

3.4 8

Streptococcus (60.4)

Lactococcus (9.0)

Klebsiella (6.1)

Enterobacter (4.2)

2.5 2

Streptococcus (70.8)

Lactococcus (12.5)

EscherichiaShigella (6.8)

Lactobacillus (1.8)

3.3 8

Pectobacteriu m (34.0)

Serratia (16.1)

Yersinia (15.2)

Pantoea (9.2)

3.3 3

Lactococcus (41.7)

Leuconostoc (19.0)

Streptococcu s (9.9)

Lactobacillus (7.0)

Other s (22.2)

1.9 4

Lactococcus (86.1)

Streptococcu s (3.5)

Lactobacillus (1.7)

Enterococcus (1.6)

Other s (6.9)

Oaxaca (OAX)

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Canasta (CAN)

Asadero (ASA) Manchego (MAN)

IP

CR

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AN

M

ED

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Jocoque (JOC)

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Panela (PA)

Lactococcus (8.8)

Vibrio (3.8)

β

Aeromonas (0.8) Lactococcus (2.3) Lactobacillus (4.1) Celerinatantimon as (2.8)

β

Other s (7.9) Other s (25.3) &

$

% shown in parenthesis; others, less abundant genera and families. In case of Cincho (CIN), others are & Weissella (3.27), Lactobacillus (3.18), Enterococcus (2.13). In case of Canasta (CAN), others are Aerococcus $ (4.41), Staphylococcus (3.72), Marinomonas (2.21). In case of Asadero (ASA), others are Enterococcus (6.90), Buttiauxella (3.25), Serratia (2.52). S-W, Shannon-Wiener index was calculated as described in Materials and methods.

ACCEPTED MANUSCRIPT

Dikarya (3.1) Candida (4.7) Dikarya (4.2)

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Galactomyces (1.6) Galactomyces (1.2) Saccharomyce se (7.4)

PT

ED

M

AN

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CR

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Table 4 Most abundant Fungi genera in cheese. Name Genus (%) Galactomyces Saccharomyces Scheffersomyc Adobera-paraes (7.4) fundir (AP) (46.8) (34.9) Scheffersomyce Saccharomyce Adobera-paraYarrowia (16.3) s (63.6) s (9.7) fundir (AA) Saccharomyces Scheffersomyce Adobera-deCandida (8.6) s (37.2) mesa (AM) (41.7) Scheffersomyce Saccharomyces Candida (2.2) Cotija (COT) s (82.4) (5.9) Scheffersomyce Saccharomyce Panela (PP) Dikarya (16.7) s (74.0) s (2.6) Galactomyces Scheffersomyc Panela (PA) Dikarya (30.1) es (9.0) (49.6) Galactomyces Saccharomyces Scheffersomyc Jocoque (JOC) es (1.0) (68.2) (27.5) Saccharomyces Hanseniaspora Kazachstania Doble-Crema (CHP) (79.4) (3.5) (2.8) Galactomyces Saccharomyces Scheffersomyc Ranchero (RED) es (3.7) (48.9) (38.9) Galactomyces Scheffersomyce Saccharomyce Ranchero s (4.5) s (1.3) (RVER) (91.8) Galactomyces Saccharomyce Candida (1.3) Zacatecas(ZAC) s (1.9) (95.4) Galactomyces Saccharomyces Scheffersomyc Chihuahua (CHI) es (7.6) (47.2) (33.7) Saccharomyces Scheffersomyc Candida (3.4) Cincho (CIN) es (1.9) (87.2) Scheffersomyce Saccharomyces Galactomyces Oaxaca (OAX) s (67.3) (18.8) (4.6) Galactomyces Saccharomyces Scheffersomyc Canasta (CAN) es (7.9) (47.2) (34.0) Scheffersomyce Galactomyces Dikarya (1.9) Asadero (ASA) s (57.6) (35.8) Scheffersomyce Galactomyces Saccharomyce Manchego (MAN) s (31.6) s (24.8) (28.1)

AC

CE

% of Relative abundance shown in parenthesis.

Candida (0.5) Candida (2.4) Hanseniaspora (2.5) Candida (0.9) Scheffersomyc es (0.8) Dikarya (2.8) Galactomyces (1.6) Candida (2.9) Dikarya (2.5) Saccharomyce s (1.4) Dikarya (4.4)

others (7.8) others (5.7) others (8.3) others (7.9) others (5.5) others (3.9) others (2.8) others (11.9) others (6.0) others (1.5) others (0.6) others (8.7) others (5.9) others (6.4) others (8.4) others (3.3) others (11.1)

ACCEPTED MANUSCRIPT Table 5 Most abundant Fungi species in cheese. SW

Species (%)

1.6 6

G. reessii (46.8)

S. cerevisiae* (17.5)

Adobera-parafundir (AA)

2.1 6

S. stipitis (63.6)

Y. lipolytica (16.3)

Adobera-de-mesa (AM)

1.8 1

S. stipitis (37.2)

S. cerevisiae (33.6)

Cotija (COT)

1.6 5

S. stipitis (82.4)

S. cerevisiae* (3.6)

1.7 6

S. stipitis (74.0)

Dikarya (16.6)

&

Panela (PP)

2.1 4

G. reessii (49.6)

Dikarya (30.1)

&

Panela (PA)

Jocoque (JOC)

1.7 6

G. reessii (68.2)

S. cerevisiae* (16.0)

Doble-Crema (CHP)

1.8 0

S. cerevisiae (49.7)

Ranchero (RED)

1.4 6

G. reessii (48.9)

Ranchero (RVER)

2.1 6

G. reessii (91.8)

S. stipitis (4.5)

Zacatecas (ZAC)

1.1 4

G. reessii (95.4)

Candida sp. (1.2)

1.0 7

G. reessii (47.2)

S. cerevisiae (17.7)

$

Chihuahua (CHI)

S. cerevisiae* (66.0)

S. cerevisiae (21.2)

$

CR

AN

US

S. stipitis (9.0)

S. cerevisiae* (29.7)

M

ED

PT

CE 2.2 0

AC

Cincho (CIN)

$

$

S. $ cerevisiae (17.4) S. cerevisiae* (3.3) S. cerevisiae* (8.0) S. $ cerevisiae (2.3) S. $ cerevisiae (1.8)

S. cerevisiae (29.7)

$

S. $ cerevisiae (11.5) H. osmophila (3.5) S. cerevisiae* (9.1) S. $ cerevisiae (0.7) S. $ cerevisiae (1.0) S. cerevisiae* (16.0) S. stipitis (1.9) S. $ cerevisiae (5.4) S. cerevisiae* (15.4)

Oaxaca (OAX)

0.8 1

S. stipitis (67.3)

S. cerevisiae* (13.4)

Canasta (CAN)

1.7 9

G. reessii (47.2)

S. cerevisiae (18.6)

Asadero (ASA)

1.9 6

S. stipitis (57.6)

G. reessii (35.8)

Dikarya (1.9)

Manchego (MAN)

1.6 3

S. stipitis (31.6)

G. reessii (28.1)

S. $ cerevisiae (14.2)

$

S. stipitis (7.4) C. naeodendra (2.7) C. naeodendra (6.9) F. oxysporum (3.1)

T

Adobera-parafundir (AP)

IP

Name

&

others (10.9) others (14.1) others (14.3) others (8.6)

G. reessii (1.2)

others (6.4)

S. $ cerevisiae (5.2)

others (6.1)

S. stipitis (1.0)

others (3.3)

K. aquatica (2.8)

others (14.3)

S. stipitis (3.7)

others (8.6)

C. naeodendra (0.7) S. cerevisiae* (1.0)

others (2.3) others (1.4)

S. stipitis (7.6)

others (11.5)

C. sagamina(1. 8)

others (9.1)

G. reessii (4.6)

others (9.3)

S. stipitis (7.9)

others (10.9)

S. $ cerevisiae (0.8) S. cerevisiae* (10.6)

others (3.9) others (15.5)

% of abundance is shown in parenthesis. G. reessii, Galactomyces reessii; S. cerevisiae*, Saccharomyces $ cerevisiae (baker’s yeast); S. cerevisiae , S. cerevisiae_rm11-1a; S. stipitis, Scheffersomyces stipitis; Y.

ACCEPTED MANUSCRIPT

AC

CE

PT

ED

M

AN

US

CR

IP

T

lipolytica, Yarrowia lipolytica; H. osmophila; Hanseniaspora osmophila; K. aquatic, Kazachstania aquatic; C. sagamina, Candida sagamina; C. naeodendra, Candida naeodendra; F. oxysporum, Fusarium oxysporum f. & sp. lycopersici 4286. Dikarya , subkingdom of fungi. S-W, Shannon-Wiener index was calculated as described in Materials and methods.

ACCEPTED MANUSCRIPT

Taxa

IP

T

Bacillus_cereus (Firmicutes) Clostridium (Firmicutes) Pseudomonas (Proteobacteria) Paenibacillus (Firmicutes) Lactococcus (Firmicutes) Lactococcus (Firmicutes) Lactococcus (Firmicutes) Lactococcus (Firmicutes)

CE

PT

ED

M

AC

Graphical Abstract

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Stenamoeba limacina Uncultured fungi Uncultured fungi Candida_sp._bg02-5-30-009a-1 Candida solani Candida drimydis Millerozyma farinosa Scheffersomyces stipitis Pachysolen_tannophilus Candida_lassenensis Candida_sp._nrrl_y-7574 Ambrosiozyma_cicatricosa Candida_kashinagacola Williopsis_salicorniae Saccharomycopsis_vini Debaryomyces_sp Phaeosphaeria_nodorum_sn15 Pichia_alni Myxozyma_nipponensis Williopsis_pratensis Pichia_dryadoides Candida_quercitrusa Candida_sp._bcmu_bx01

US

AN

Table 6 List of taxa with their OTUs ID for Figure 6 Number OTUs_ID Image A; Bacterial Taxa B01 KF625179.1.1776 B02 AF018036.1.1512 B03 AM491464.1.1523 B04 AB428571.98.1656 B05 OTU10127 B06 AM944736.1.1429 B07 BCVN01000061.3283.4819 B08 OTU10873 Image A; Fungal Taxa F01 41135 F02 100023 F03 14916 F04 87287 F05 7260 F06 101043 F07 71176 F08 96648 F09 71004 F10 105830 F11 109417 F12 50314 F13 46395 F14 134 F15 99356 F16 14030 F17 4269 F18 106439 F19 94711 F20 81147 F21 112792 F22 99621 F23 39901

ACCEPTED MANUSCRIPT Highlights



Bacterial and fungal communities in Mexican cheeses are wide and diverse.



Some identified bacteria and fungi belong to genera with potential

Members of the microbiota could be associated to the manufacture

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

T

pathogenic members.

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PT

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M

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There are bacterial and fungal core communities among Mexican cheeses.

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

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environment.

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6