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There have been many times in my life (especially since I've had kids) that I've had to compromise with very short-burst, micro workouts. The trouble? Most people dismiss micro workouts.
Many people wrongly assume that these types of workouts are the ultimate compromise, only to be used when absolutely necessary. Over the last few years, I've found that this conclusion is wrong.
The key to making micro workouts effective is to utilize the same principles you'd use if you were designing a traditional workout program for the gym:
- Maintain a weekly volume of 10-20 work sets per movement pattern
- Maintain an optimal frequency of at least 2x per week per movement pattern
- Dial in your recovery methods by eating and sleeping to support your goals
If you're familiar with traditional lifting programs, these guiding principles will sound like nothing new, and that's the point. The key is to find extremely time-efficient methods of accomplishing the same thing you would in the gym.
What exactly is a micro workout?
Discussions on micro workouts are often complicated by the fact that the term "micro workout" is loosely defined.
For our purposes, the term "micro workout" will be applied to short mini-bouts of exercise lasting anywhere from 3-10 minutes. These can include anything from antagonistic supersets or circuits of traditional resistance training exercises to Tabata-style cardio.
They are usually intended to be done daily or multiple times throughout the day.
So, are micro workouts actually effective?
Studies have shown that micro workouts throughout the day are an effective alternative to traditional exercise. One 2018 study of daily 6-minute micro-sessions showed improvements in functional strength of 7.8-20.9% over 4 weeks.
This 2013 article in ACSM's Health & Fitness Journal noted that: "HICT seems to be an efficient means of exercise to help decrease body fat, improve insulin sensitivity, and improve V˙O2max and muscular fitness."
The key to making them effective is to utilize extremely time-efficient methods of following the proven principles of exercise.
Benefits of micro workouts
If we're following evidence-based principles for weekly volumes, intensity, and frequency, we can expect micro workouts to produce very similar results to basic resistance training using calisthenics, resistance bands, or dumbbells.
What's more, micro workouts have the advantage of making a regular exercise routine extremely accessible to those who struggle to find time for fitness. By picking simple, accessible exercises, like dips and pull ups, we save time and make it possible to do our workouts virtually anywhere.
They are best used by people who want to reap the rewards of being in shape with minimal time and effort; for this goal, they are a near-perfect solution.
Of course, the "effectiveness" of a given protocol will vary based on the individual's goal. As noted in our "limitations" section below, if your goal is to compete in a bodybuilding show, then micro-workouts are unlikely to get you there.
Micro Workout Examples
The sample workouts below reflect a method of designing micro workouts that I've used on myself and given to others many times. You can use them as written, or you can design your own – rest assured that if you follow the basic, proven principles of exercise, you'll accomplish roughly the same result that you could expect from traditional workouts.
Upper body micro workout (3-4 minutes)
Where the upper body is concerned, one single exercise won't cut it. While the basic pushup or parallel bar dip is a fantastic exercise for building the chest and triceps, it leaves out the upper back, biceps, forearms, etc. So, in order to cover the upper body, we're going to need to utilize a compound pressing exercise and a compound pulling exercise of some sort. Here's one of my favorites:
- Pick two exercises, a push and a pull. Make them accessible with minimal equipment. My favorites would be a push up variation and a seated resistance band row.
- Determine your "rep max" for each exercise (while maintaining good form). Divide that number by 3 to determine what your "training set" number will be. Note: you will likely need to test your maxes in advance of starting a program.
- Complete 4 training rounds of each exercise, back-to-back, with no breaks. On the last set, perform an AMRAP set (as many reps as possible).
- Repeat 3-5 times per week.
- Every 2 weeks, re-test your maxes and adjust your "training set" numbers accordingly.
I've used this method a lot in my own training, and I've suggested it to others. The whole thing should take around 3 minutes.
Lower body micro workout (3-4 minutes)
The lower body is a bit trickier, since the muscles are much larger and stronger. The key here is to utilize unilateral (single-leg) variations of popular exercises. Don't worry, we're not going to be doing any party-trick exercises. Just proven, straightforward resistance training staples:
- Pick a single-leg, knee dominant squat variation, and a hip dominant exercise. My personal favorites would be the Bulgarian split squat and resistance band deadlift (band under feet, ends in hands).
- Determine the max number of reps you can do in 2 minutes on each exercise. Stop when the time is up or if your form breaks down. Divide that number by 3 to determine your "training set" number.
- During your workouts, complete 4 rounds of training sets, and on the last set, complete AMRAP in 1 minute.
- Repeat 2-4 times per week.
- Every 2 weeks, re-test your maxes and adjust your "training set" numbers accordingly.
I've included time limits here because the muscles of the legs are strong. It's unlikely that you'll hit true muscular failure in the hamstrings, glutes, and quads on these exercises like you would if you were completing a 5RM on a barbell back squat.
Core micro workout (3-6 minutes)
My favorite way to design a micro workout for the core involves planks. I am aware that the humble plank gets a lot of flak online. It seems to me that most people who disparage planks don't really understand how to maintain tension in the midsection during the exercise. I've found that planks, when done properly, are capable of producing an iron clad, strong, pain-free midsection in almost everybody. Try this:
- 1 min plank
- 1 min side plank
- 1 min side plank (switch sides)
Repeat this circuit for up to 3 rounds, if you've got the guts. Most people will have trouble getting through 2 rounds of this without a break (or losing tension). Some will struggle with one round. That is perfectly OK.
Cardio micro workout (4 minutes)
There's no sense in re-inventing the wheel here. Most of us are aware that high intensity interval training (HIIT) is one of the best ways to shorten a cardiovascular workout while maintaining the positive effect we'd get from cardio.
But is it possible to get a training effect in 3-5 minutes? If you've never tried Tabata before, prepare to be humbled:
- Pick your cardiovascular endurance exercise of choice: sprints, burpee and pull-up supersets, double unders (jump rope), whatever you want.
- Perform 20 seconds of the exercise in "sprint" fashion – full effort
- Rest 10 seconds
- Repeat 8 times (for a total of 4 minutes)
Four minutes doesn't seem like a long time before you try your first Tabata workout. Pro tip: leave this one for after or before work. You will be sweaty when it's over. You have been warned!
Planning and programming micro workouts
The utility of a micro workout program is that they are extremely time efficient. That being said, you still need a plan. This is where most people get it wrong. Working out willy-nilly is never the answer.
Here are a couple of ways you could structure a weekly program around micro workouts:
Option 1: Micro Workouts Throughout the Day
AM (before work) | PM (after work) | PM (before bed) | |
M | Upper body | Lower body | Core |
T | Upper body | Lower body | Core |
W | Tabata | – | – |
Th | Upper body | Lower body | Core |
F | Upper body | Lower body | Core |
Sa | Tabata | – | – |
Su | – | – | – |
This may be my favorite option. Considering that all of the above workouts last 3-6 minutes, you can sneak an entire exercise program into your week with very little time commitment this way.
Option 2: Combining Micro Workouts
AM (before work) | PM (after work) | PM (before bed) | |
M | Upper / lower | Lower body | Core |
T | Upper / lower | Lower body | Core |
W | Tabata / core | – | – |
Th | Upper / lower | Lower body | Core |
F | Upper / lower | Lower body | Core |
Sa | Tabata / core | – | – |
Su | – | – | – |
This option has you performing a 7-10 minute workout every morning, 6 days per week. Of course, you don't have to do it in the morning – you could just as easily squeeze it in after work or after the kids go to bed.
The limitations of micro workouts
I'm well aware that I've talked up micro workouts quite a bit in this article. I'd be remiss if I didn't at least mention the drawbacks:
If your goal is to have the ultimate physique, micro workouts probably aren't for you.
The most obvious drawbacks are likely the fact that you won't be maximizing anything, necessarily. While compound exercises done close to failure two or more times per week are great for general hypertrophy, you're going to want to add some isolation exercises if maximal hypertrophy is your goal.
If your goal is to be as strong as possible, micro workouts probably aren't for you.
Similarly, for strength goals, micro workouts will fall short. That is to say, if your goal is to bench 315, you'll have to go to a gym and strength train under a barbell at some point.
If distance-running or endurance is your goal, micro workouts likely won't get you there.
If you want to set a new 10K PR, you'll likely need to participate in true 10K training. One caveat is that if you're struggling to find time for resistance training as a distance runner, micro workouts can be an excellent option for you to squeeze some resistance training into your busy schedule.
Time to get working!
If you struggle to find the time to work out or you simply aren't interested in becoming a gym rat, 3-5 minute micro workouts throughout the day may be the perfect option for you. Now that there are no more excuses, time to get working!


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Name | Rebecca Applin |
Biography | Becky is currently the holder of the Cameron Mackintosh Resident Composer Award and is resident composer at the Mercury Theatre, Colchester and the New Wolsey Theatre, Ipswich. As part of the scheme she has composer for Sandi Toksvig's 'Bully Boy' at the Mercury and 'Alfie Strange: Trained Time Travellers Only' at the New Wolsey. She is currently working on 'Wind in the Willows' at the Mercury and will be composing for 'Much Ado About Nothing' there in the Autumn. She will then be composing for 'The Twits' at the New Wolsey. Both theatres are currently mentoring her through creating the musical 'My Life', a contemporary adaptation of the Faust legend. TV and Radio credits include: 'I Know Me' (BBC Learning and Gamelab, BAFTA nominated), 'Wanna Be a Rockstar' (BBC Learning and Gamelab, BAFTA nominated), 'Dance with the Elements' (BBC Learning and Gamelab), 'Vanishing Point' (Youth Music Theatre and Gamelab), 'Death in Genoa', 'The Lost World of the Suffragettes' (Radio 4 Archive Hour), 'Don't Cry for me Maradona' (Radio 5 Live), 'John Stapleton's History of Manchester' (all Made in Manchester Radio). |
Website | |
Writer Type | Lyricist, Composer |

subset: commoncrawl


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23 Jul Irvingia gabonensis
Scientific name: Irvingia gabonensis Aubry-Lecomte ex O'Rorke Baill.
Family: Irvingiaceae.
Distribuiton/conservation status: widely distributed and relatively common in moist lowland rainforest, also occurring in semi-deciduous forest, especially in association with human habitation. Near-threatened (NT) due to forest clearance and degradation, and poor natural regeneration.
Common names: Bush mango, dika nut (English), Ogbono (Igbo), Oro, Oyin (Yoruba), Ogwe, Ohere (Edo)
Fruits/seeds: ovoid, green and sweet-smelling when ripe, with orange juicy pulp containing one seed.
Fruiting time: July – August.
Seed collection: collect fruits from under the parent tree and bury in sawdust for 5 – 7 days. This softens the fruits, making it easier to separate seeds from pulp.
Type of seed: recalcitrant.
Sowing method: sow seeds individually in pots at a depth of 3 – 4cm.
Sowing medium: cured sawdust or topsoil from under the parent tree.
Germination period: 14 days.
Germination percentage: 65 – 70%.
Growth/development: seedlings require complete shade for optimum growth and can be planted out 8 weeks after germination. Trees begin to fruit when c. 4 years old.
Notes: protect seeds and seedlings from rodents.


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Please note: Information available under Archived Committees is offered for reference purposes only, as these committees are no longer active.
The Public Safety Standing Committee has merged with the Environment & Transportation Standing Committee. Effective October 1, 2012 the standing committee will be known as the "Environment, Transportation & Public Safety Standing Committee".
Visit the City Council Meetings page.
Council Services Department350 City Hall Square West, Room 203Windsor, OntarioN9A 6S1CanadaPhone: For general inquiries, call 311. For detailed inquiries, call (519) 255-6100.Fax: (519) 255-6868Email: firstname.lastname@example.com


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Holders of those visas are nonetheless required to use for the Thailand Pass at the MFA web site. Spending on company journey, stay leisure, and in-person events must be restored by providing tailored tax reduction. Temporary tax credit and deductions are included within the Hospitality and Commerce Jobs Recovery Act, which are intended to spice up spending and pace up the recovery course of. The CDC recommends not to travel internationally till you are absolutely vaccinated. Before you journey, get examined with a viral take a look at 1-3 days before your trip.
In addition to classifying tourism by elements similar to geography, possession, and performance, tourism can be categorised by the type of vacationer and their relationship to the nation visited. Many international locations have a minister of tourism, responsible for advocating for tourism development throughout the country. The United States does not have such a role; as an alternative, the agency that's the main body for promoting tourism throughout the United States is __________. It additionally provides a chance to develop new marine tourism offerings targeted on the expanding client demand for wellness services and products. To generate information on home coastal and marine tourism in Ireland SEMRU carried out a family survey of residents in 2019, funded by the Marine Institute via its Marine Research Programme. As well as expenditure patterns the survey additionally examined participation charges amongst home residents in quite lots of marine actions and the place Irish residents went for overnight coastal visits within the reference year 2018.


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Los Angeles Chargers release former Ohio State standout QB
Cardale Jones' entire football journey has been an interesting one.
Jones of course played his college ball at Ohio State. He had an odd road to stardom there, but he of course showcased his potential by winning a national title with the Buckeyes.
Sports Betting in Big Ten Country
With the launch coming on January 1, 2023, Ohio sports betting apps are almost here.
FanDuel is now giving users a $100 bonus for Ohio pre-registration. Go pre-register now.
21+ and present in OH. Gambling Problem? Call 1-800-GAMBLER.
The 6-foot-5 gunslinger is also famously known for this tweet:
Remember that time he said "we ain't come here to play school?"
Cardale Jones just graduated from Ohio State: https://t.co/o6oql5BDpR pic.twitter.com/eoyZ4rifF1
— SportsCenter (@SportsCenter) May 7, 2017
As SportsCenter mentioned on Twitter in 2017, Jones eventually graduated from Ohio State. That was odd.
Jones' future in the NFL didn't hold a ton of success early, though he was drafted in the fourth round by the Buffalo Bills. He eventually got traded to the Chargers for a draft pick and on Sunday, it was announced that the former Buckeye was being released:
The #Chargers are releasing QB Cardale Jones, source said.
— Ian Rapoport (@RapSheet) September 2, 2018
What's next for Jones? We'll have to wait and see.
Whether he latches onto another NFL team or makes a move to the CFL, the talent to play football is there.


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Tired of the same old grilled or fried pork for Sunday lunch and dinner? Why not try this boiled pork tenderloin recipe? It's simple, easy, and definitely mouthwatering. Despite its simplicity, this absolutely filling dish will be so memorable, it will definitely be a staple to every meal.
All you need to do is get some tenderloin and your stock pot. It will take just a couple of hours to make this scrumptious dish. The tenderness of the meat, topped with a sweet and salty sauce is a gastronomic experience waiting to happen. The addition of the white wine will definitely kick this tenderloin recipe up in a notch.
Don't be afraid to use any brand of white wine for this recipe. Serve it with wine or juice, the boiled tenderloin pork dish will absolutely be an amazing dining experience. For more tenderloin recipes, you might want to check out our Grilled Teriyaki Pork Tenderloin as well.
If you are looking for more pork recipes, check out our list of easy pork recipes!
How To Make Boiled Pork Tenderloin
Add a twist to your usual tenderloin by using white wine to unleash a tangy and sweet flavor.
- 2 lb pork tenderloin
- 3 tbsp vegetable oil
- 1 tsp dried thyme
- 1 tsp garlic powder
- ¼ cup white wine
- 4 cabbage wedges, chopped
- 1 cup red onion, diced
- 1½ cups potatoes, diced
- 1 cup chicken broth
- salt & ground black pepper, to taste
- Season with salt, pepper.
- In a large deep skillet, sear pork in vegetable oil until brown.
- Add thyme and deglaze with white wine. Reduce briefly.
- Set aside the pork.
- Using the same pan, saute onions and potatoes briefly.
- Add the chicken broth & garlic. Simmer until potatoes are tender, roughly 20 minutes.
- Place the pork back & add the cabbage. Simmer for another 10 minutes.
- Before serving, slice the pork into ½-inch then top with vegetables.
- Serve and enjoy.
Recipe Notes
Cutting pork into smaller pieces is the secret to having a flavorful meal. Having smaller pieces of pork makes it easy to season and cook the meat evenly.
- Sugar: 16g
- :
- Calcium: 202mg
- Calories: 340kcal
- Carbohydrates: 36g
- Cholesterol: 74mg
- Fat: 10g
- Fiber: 13g
- Iron: 4mg
- Potassium: 1441mg
- Protein: 30g
- Saturated Fat: 6g
- Sodium: 252mg
- Vitamin A: 445IU
- Vitamin C: 178mg
Frequently Asked Questions
How can I keep the tenderloin moist?
To keep the pork tenderloin from completely drying out during cooking time, it is best to make sure you have a good sear on the pork pieces, and also keep the temperature low while simmering. By doing this, we are allowing the crust to keep the moisture inside the meat without it losing its shape. Cooking the pork for long over low temperatures ensures that the juices aren't pushed out of the meat while cooking.
Is there any difference between the common white wine and the cooking wine?
Yes, there is, in fact, quite a difference between your regular white wine and cooking wine. For instance, flavor-wise, the regular white wine will produce a stronger taste when you use it for cooking, such as in this recipe. On the other hand, cooking wine has a more neutral taste that will be useful for just cooking and not drinking.
You don't need to find an excuse to enjoy this tasty boiled tenderloin pork dish. Serve it with your favorite bowl of mashed potatoes or some rice, and we guarantee it's an absolutely filling dish.Have your own special recipe to share? Submit Your Recipe Today!


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Transports & access
Autoroute A6, Paris-Lyon, Autoroute A43, Exit 27 Hermillon
St Jean de Maurienne TGV train station
Lyon - St Exupéry airport
Preferential rates for buses
Azureva Les Karellis : a mountain holiday village 100% families, at the foot of the slopes
Skiing + holidays + family = the Les Karellis*** holiday village in the Savoie! From our club-village located at an altitude of 1,600 m, you can get to the amazing area of Karellis on skis or on foot. A magnificent natural setting awaits. And you'll be glad to know, you can get to the ski lifts on foot from the club-village. The slopes spread out over 530 ha, with varying levels, undulating countryside, and well maintained bends: With 70% of ski slopes above 2000 m, you'll be amazed! The Les Karellis*** holiday village is a skiing holiday village in the fantastic Savoie region, which you can visit for as long as you like from the start of the season until April! With full board or half-board, you will love the ambiance, often described by our guests as authentic, warm and friendly. The whole family will enjoy it, thanks to 3 kids and teens clubs. Our qualified activity leaders are not short of ideas for après-ski and evening activities. Their activities and parties will leave you with some amazing memories!
At the foot of the ski slopes + Fees Included
Direct access to ski lifts. Fees INCLUDED in the price of your holiday in half-board and full-board only. Ski lockers.
Relaxation and spa
Fantastic relaxation space with whirlpools, sauna, hammam and massage (optional extra).
Holiday magic with your family
Special Christmas Eve & New Year's Eve dinner, included for your week boarding holidays in our village. Festive atmosphere and animations throughout the evening.
In live
Forfaits remontées mécaniques
Ménage fin de séjour
Linge de toilette
Casiers sécurisés (ski, vélo...)
Réveillons Noël/Nouvel An
Entertainment Multi Clubs for children: 3-11 years old, 12-14 years old and 15-17 years old
- Open 5 days a week during
French school holidays, framed
by qualified animators and according to the
number of participants.
- 1 vigil
- 1 theme day
- 1 special animation
- 1 toy library and 1 library.
Animations during the opening period of the establishment during the French school holidays.
From 3 to 17 years old.
During school holidays and depending on the number of participants.
Open 6 days/week
Activities adapted to each age
1 vigil/week
1 continuous club day (meals included in full board)
1 teen outing/week
Activities offered during French school holidays. Open according to the participation of a minimum number of children.
Azureva reserves the right not to accept your child if the legal limit on the number of children/animator is free.
Do not hesitate to inquire at the reception of our club to find out if the club will be open on the dates of your stay.
Fitness room.Table tennis, billiards.Dance, stretching and yoga classes.Pre-dinner drinks and games, coffee and games.
Exploring the slopes, walks, snowshoe walks led by our staff or ESF guides.
Shows, concerts, orchestras, cabaret, dance, etc.
Ski area 1 600 m to 2 550 m above sea level, well equipped with snow cannons. 28 slopes over 60 km for all levels: 5 green, 9 blue, 10 red, 4 black 17 ski lifts: 8 platter lifts, 6 fixed chairlifts, 2 detachable chairlifts, 1 rope tow, slalom slope, ESF skiing lessons for all the family. Disabled skiing lessons with qualified instructors. 6-person detachable chairlift with heated seats, for skiers and pedestrians (the only one of its kind in France). This chairlift takes you from the centre of the resort to 2 200 m above sea level in 6 minutes!
Ski area 1 600 m to 1 800 m above sea level.Tailor-made circuits. Classic and skate skiers have free access to 30 km of cross-country skiing trails.
Snowpark 2 250 m to 2 300 m above sea level, exposed to the sun, chairlift nearby. Boardercross course on a separate slope.
New: the Yooner and Snowscoot are here, for your snow-riding enjoyment!10 km of waymarked footpaths.100 m sledging slope below the 'Vinouve' heated chairlift, for all ages. Children's snow play area.Sled dogs.
Autoroute A6, Paris-Lyon, Autoroute A43, Exit 27 Hermillon
St Jean de Maurienne TGV train station
Lyon - St Exupéry airport
Preferential rates for buses


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- Research
- Open access
- Published:
Expanded catalogue of metagenome-assembled genomes reveals resistome characteristics and athletic performance-associated microbes in horse
Microbiome volume 11, Article number: 7 (2023)
As a domesticated species vital to humans, horses are raised worldwide as a source of mechanical energy for sports, leisure, food production, and transportation. The gut microbiota plays an important role in the health, diseases, athletic performance, and behaviour of horses.
Here, using approximately 2.2 Tb of metagenomic sequencing data from gut samples from 242 horses, including 110 samples from the caecum and 132 samples from the rectum (faeces), we assembled 4142 microbial metagenome-assembled genomes (MAG), 4015 (96.93%) of which appear to correspond to new species. From long-read data, we successfully assembled 13 circular whole-chromosome bacterial genomes representing novel species. The MAG contained over 313,568 predicted carbohydrate-active enzymes (CAZy), over 59.77% of which had low similarity match in CAZy public databases. High abundance and diversity of antibiotic resistance genes (ARG) were identified in the MAG, likely showing the wide use of antibiotics in the management of horse. The abundances of at least 36 MAG (e.g. MAG belonging to Lachnospiraceae, Oscillospiraceae, and Ruminococcus) were higher in racehorses than in nonracehorses. These MAG enriched in racehorses contained every gene in a major pathway for producing acetate and butyrate by fibre fermentation, presenting potential for greater amount of short-chain fatty acids available to fuel athletic performance.
Overall, we assembled 4142 MAG from short- and long-read sequence data in the horse gut. Our dataset represents an exhaustive microbial genome catalogue for the horse gut microbiome and provides a valuable resource for discovery of performance-enhancing microbes and studies of horse gut microbiome.
Horses (Equus caballus) are used worldwide in leisure, racing, transportation, agriculture, and forestry activities, and they are widely raised for the production of milk and animal protein in developing countries [1]. There are an estimated 59 million horses worldwide [2], with an annual economic impact of approximately $300 billion [3]. Thus, it is important to achieve a detailed understanding of horse biology to potentially improve the use of horse in human activities.
Horses have been employed as a model system for investigating digestion in herbivores with hindgut fermentation, which include donkey, zebra, rhinoceros, and elephant, and for studying ruminant caecal digestion [4, 5]. The intestinal tract of horses contains a large number of symbiotic bacteria, fungi, archaea, protozoa, and virus [6], which provide animals with the hydrolytic enzymes that convert carbohydrates into energy by fibre fermentation [7, 8]. The metabolites produced from these microbial groups in horses play important roles in host health, diseases, development, and even behaviour [9,10,11,12,13,14,15]. Prior studies have reported that the intestinal microbiota is associated with horse diseases (e.g., colitis, laminitis, grass sickness, asthmatic, diarrhoea) [16, 17] and exercise [18, 19]. Mach et al. used blood transcriptome, blood metabolome, and faecal microbiome to study horses' endurance before and after races and proposed that the gut-mitochondrial axis was associated with athletic performance [15]. Thus, an in-depth understanding of the microbial composition of the horse intestine offers opportunities for enhancing athletic performance and improving the maintenance of animal health by manipulating the microbiota through dietary intervention or the addition of probiotics.
The microbiota composition in horse gut has been partly characterized based mainly on 16S amplicon sequencing [9,10,11,12,13,14,15], Recently, a gene catalogue and hundreds of MAG of horse gut microbiome have been reported [6, 20, 21], but large-scale studies on microbiota composition and function in horses are still lacking. The emergence of high-throughput sequencing and metagenome binning technology has made it possible to obtain nearly complete metagenome-assembled genomes (MAG) on a large scale [22]. Metagenomic sequencing technology can identify a large number of previously unknown bacterial species among intestinal microbes and has been used to characterize the functions of these microbes at the genomic level [22,23,24,25,26]. This technology has generated thousands of MAG from humans [23], ruminants [24], chickens [25], pigs [26], and horse [6]. Moreover, long-read sequencing can improve the quality of assembly by increasing the continuity of genome assembly [27]. Thus, the use of high-throughput sequencing technology combined with long-read sequencing offers a promising strategy for characterizing the microbial composition and function of the horse microbiome. Moreover, performance-enhancing microbes and novel enzymes (e.g. CAZy) in the horse gut may be deeply explored by the whole-genome metagenomics [27].
In this study, we aimed to develop a microbial genome resource for research on the horse gut microbiome and to use that resource to answer questions about how the gut microbiota is related to racehorse performance. We used gut samples of 242 horses from two provinces of China. A large-scale metagenomic sequencing scan was performed to characterize microbiota composition in horse gut. Furthermore, we revealed resistome characteristics and athletic performance-associated microbes in horses. This study provides an exhaustive catalogue of MAG in horse and answers important questions about the relationship between the gut microbiome and horse performance.
Metagenomic samples
All details about experimental horses and samples are listed in Additional file 1: Table S1. A total of 242 gut samples from indigenous Yili horses, Thoroughbred horses, Tibetan horses, Shetland ponies, and Yili racehorses were collected and used in this study. These horses were raised in different counties of two provinces in China. Indigenous Yili horses (n = 110, Yili horse) and Tibetan horses (n = 10, Tibet horse) grazed on natural pastures and consumed pasture forage. Thoroughbred horses (n = 58, Thoroughbred) belonged to stabled horses and were fed a mixed forage and concentrate diet. Shetland ponies (n = 8, Shetland pony) were raised in a farm and fed a mix of pasture grasses and concentrate diet. Yili racehorses (n = 21, Yili racehorse) consumed a mix of pasture grasses supplemented with concentrate feedstuffs. These Yili racehorses were enrolled and winner in the 30-km category in the horse race of the Chinese nation. Faeces of racehorses were collected before the race. Through consulting the racehorse owner, we knew that these racehorses had different levels of training every day. A group of age-matched Yili nonracehorse (n = 35, Yili nonracehorse) was fed a mix of pasture grasses supplemented with concentrate feedstuffs and used as control group for Yili racehorses. All Yili nonracehorse have no training plan. All horses in this study were healthy and did not receive any antimicrobial treatment (antibiotic, anthelmintics, or anti-inflammatory nonsteroidal treatments) for two months before sampling. For 242 gut samples in this study, 110 caecal samples were collected from 110 indigenous Yili horses, and the remaining 132 rectal gut (faeces) samples were from 132 horses including Tibet horse, Thoroughbred, Yili racehorse, and Yili nonracehorse. All samples were frozen in liquid nitrogen, transported to the laboratory, and preserved in a freezer at −80°C until DNA extraction.
DNA extraction and quality control
To obtain high-quality microbial DNA from the gut contents, a modified hexadecyltrimethylammonium bromide (CTAB) method was used for DNA extraction [28]. Briefly, 1000 μl of CTAB lysis buffer (0.1 M Tris-HCl [pH 8.0], 1.4 M NaCl, 0.02 M EDTA, 2% CTAB, DNA- and RNA-free) was added to a 2.0-ml EP tube (DNase- and RNase-free), along with 20 μl of lysozyme (DNA- and RNA-free); a 100-mg sample was then added, and the lysis solution was incubated for 2–3 h at 65°C. For complete lysis, the sample was mixed by inversion several times during incubation. After brief centrifugation, 950 μl of the supernatant was transferred to a new 2.0-ml EP tube containing 950 μl of a phenol–chloroform-isoamyl alcohol (25:24:1, pH 8.0, DNA- and RNA-free) solution. After mixing, the sample was centrifuged at 12,000 rpm for 10 min. The supernatant was carefully transferred to a new EP tube, and an equal volume of chloroform-isoamyl alcohol (24:1, DNA- and RNA-free) was added, followed by thorough mixing and centrifugation at 12,000 rpm for 10 min. After centrifugation, the supernatant was transferred to a new 1.5-ml EP tube, a 3/4 volume of isopropanol was added to the supernatant, and the tube was placed at −20°C for 20 min to allow precipitation after mixing. The tube was then centrifuged at 12,000 rpm for 10 min, the supernatant was discarded, and the precipitate was washed twice with 1 ml of 75% ethanol. After drying, 50 μl of ddH2O was added to dissolve the DNA sample. Finally, 1 μl of RNase A was added, and the sample was placed at 37°C for 15 min to digest the RNA. The quality of the extracted DNA was checked via 1% agarose gel electrophoresis, and the integrity and potential contamination of the sample were assessed via pulsed-field gel electrophoresis. For purity determination and precise quantification, a Nanodrop Kit (Implen, CA, USA) and a Qubit® 2.0 fluorometer (Life Technologies, CA, USA) were used, respectively.
Library construction and sequencing
To prepare the Illumina sequencing library, we used the NEBNext®Ultra™ DNA Library Preparation Kit (New England Biolabs, USA) and a 1 μg DNA sample. An index code was added to the primer to allow different samples to be distinguished in the sequence data. The kit manufacturer's recommendations were strictly followed. Briefly, the extracted DNA was fragmented into 350-bp fragments via sonication, and the ends were repaired. An adenine nucleotide was then added at the ends, and full-length adaptor sequences were connected. These libraries were purified with the AMPure XP system (Beckman Coulter, Brea, CA, USA). An Agilent 2100 Bioanalyzer and real-time PCR were used for size distribution and quantitative analyses of the purified products. After the quality of the library was verified, all of the samples were subjected to paired-end sequencing by using the Illumina NovaSeq 6000 platform with a read length of 150 base pairs (PE150).
For the preparation of the PromethION library, we used an SQK-LSK109 Ligation Sequencing Kit (Oxford Nanopore Technologies, Oxford, UK) to obtain 8 μg of DNA from each sample according to the manufacturer's recommendations. Briefly, the DNA was processed by using a Megaruptor (Diagenode, NJ, USA); DNA fragments longer than 10 kb were then screened by using BluePippin. A specific barcode was added to the fragments that had been repaired, an A tail was also added, and the length of the fragments was checked. To complete the preparation of the DNA library, samples with different barcodes were mixed in equimolar amounts and purified, and the DNA concentration was quantified by using a Qubit fluorometer. After the quality of the library was verified, nanopore sequencing technology was used for sequencing.
Data quality control
For the quality control of the raw data obtained from the Illumina sequencing platform, Readfq ver. 8.0 software was used to filter out low-quality reads with ambiguous "N" bases (More than 10 consecutive N bases) and adapter contamination (the overlap of the adapter sequence exceeds 15bp) with the parameters '--Q 53,40 --C 53,40 --N 10 --alen 15 --amis 3 --dup (--amis: cut-off adapter mis-match bases ; --dup: filter duplications)' [29]. Briefly, the quality value filter value is set to Q20. Alignment was performed with Bowtie 2 software (version 2.2.4, http://bowtie-bio.sourceforge.net/bowtie2/index.shtml) with the parameters '--end-to-end, --sensitive, -I 200, -X 400' [30], and reads aligned to the horse genome (EquCab3.0: GCA_002863925.1) were removed. The remaining high-quality reads were further analysed.
For the Nanopore sequencing data, we used Guppy software base calling to convert the data from fast5 format into fastq format. NanoPlot ver. 1.18.2 (https://github.com/wdecoster/NanoPlot/) was used to perform quality control on the fastq-format data; the threshold was set to Q > 7, and the parameters were set to '-t 20, --loglength, --N50' [31]. In addition, we used BLASTR ver. 5.1 software with the parameters '--nproc 30, --bestn 10, --nCandidates 10, --noSplitSubreads, --maxScore -1000, --maxLCPLength 16' to compare our data with the horse genome to filter out reads that might have originated from the horse host [32]. Reads longer than 500 bp constituted the final valid dataset.
Metagenomic assembly and binning
SOAPdenovo2 ver. 2.04 software was used with the parameters '-d 1, -M 3, -R, -u, -F, -K 55' [33] to assemble clean data from the Illumina sequencing results and to obtain scaffolds. The assembled scaffolds were then interrupted at the N junction to obtain scaftigs, and fragments shorter than 500 bp were simultaneously filtered out to obtain high-quality scaftigs [30]. MetaWRAP ver. 1.2.1 software (https://github.com/bxlab/metaWRAP) was subsequently used for metagenomic binning. In brief, the assembly was binned with the metaWRAP binning module by using the metagenomic binning programs MaxBin2, metaBAT2, and CONCOCT. The metaWRAPBin refinement module was applied to consolidate multiple binning predictions into a new, improved bin set [34]. All of the final bins were aggregated, and dRep ver. 1.1.2 software was then used with the parameters '-p 16, -comp 80, -con 10, -str 100, -strW 0' [27] to remove duplicate bins. Then, dRep was used with the secondary clustering at the threshold of 99% ANI with at least 25% overlap between genomes. CheckM software ver. 1.0.7 was used to evaluate the quality of the assembled bins, which were screened according to the criteria of completeness ≥50% and contamination ≤10% (4142 medium-quality MAG) [35, 36]. Only bins assessed by CheckM as complete ≥80% and contamination ≤10% were further screened as high-quality MAG. For duplicate bins, bin scores were given as completeness − 5 × contamination + 0.5 × log(genome N50); the MAG with the highest score was retained. After analysis, 2272 MAG were retained in the assembled data (2240 MAG were assembled from the Illumina sequence data and 32 from the Nanopore sequence data). The metawrap quant_bins module was used with options 'metawrap quant_bins -b genomes/ -o QUANT_BINS/' to calculate the abundance of MAG in each sample [34].
Flye ver 2.4.2 2 software was used to assemble clean data from the Nanopore sequencing results with the parameters '--threads 4, -- meta, -g 5m' [37]. Finally, the Illumina sequencing data were used to correct the Nanopore data, and the preprocessed clean data were compared to the scaftig data to obtain unused PE reads with the parameters '--end-to-end, --sensitive, -I 200, -X 400'. After scaftigs less than 2 Mb long were filtered out [38], the assembled scaftigs were subjected to statistical analysis.
Finally, PhyloPhlAn ver. 3.0.51 software [39] was used to construct a phylogenetic tree of the 4142 assembled MAG. RNAmmer ver. 1.2 software [40] was used to predict the 16S rRNA genes, and tRNAscan-SE ver1.3.1 [41] was used to predict tRNA genes. The ANI was calculated by using PYANI ver. 0.2.10 with the parameters '-m, ANIb' [42].
Gene catalogue construction, taxonomic annotation, and abundance profiling
MetaGeneMark (prokaryotic GeneMark.hmm ver. 2.10; http://topaz.gatech.edu/GeneMark/) [43] was used to predict all open reading frames (ORFs) of the assembled scaftigs (≥ 500 bp). Then, a nonredundant gene catalogue was then constructed by using CD-HIT ver. V4.5.8 software (http://www.bioinformatics.org/cd-hit) with greater than 95% identity over 90% of the shorter ORF length clustered together by a greedy pairwise comparison implemented. The longest ORF from each group was selected as the representative of the group. CD-HIT with default parameters during analysis except '-G 0, -aS 0.9, -g 1, -d 0, -c 0.95 b -n 5' [44]. The uniqueness of our gene catalogue was assessed by clustering with the reported equine gut gene catalogue using the same parameters. To determine the abundance of genes and reads, these sequences were mapped to the gene catalogue (unigenes) by using Bowtie ver. 2.2.4 with the parameters '--end-to-end, --sensitive, -I 200, -X 400'. The genes with ≤2 reads in each sample were filtered out, and the gene catalogue was ultimately used for subsequent analysis [45]. The abundance of genes was calculated by counting the number of reads and normalizing result according to gene length.
The unigenes were aligned to the integrated NR database (2018-01-02) by using DIAMOND ver. 0.9.9.110 with the parameters '-k 50, -sensitive, -e 1e-5' [46]. For the final aligned results of each gene, significant matches were defined according to an e-value ≤ 10×e-value of the top hit, and the taxonomic level was determined by using the lowest common ancestor-based algorithm, implemented in MEGAN [47]. The abundance of a taxonomic group in each sample was equal to the sum of the abundance of genes annotated to a feature [48].
Metagenomic assignment
ORFs were predicted from the assembled MAG by using MetaGeneMark (prokaryotic GeneMark.hmm, ver. 2.10) [49]. All of the predicted genes were aligned with the integrated NR database by using DIAMOND ver. 0.9.9.110 (https://github.com/bbuchfink/diamond). In addition, GTDB-Tk (v.1.3.0) was used to assign the taxonomy of the MAG [50].
Proteome analysis
DIAMOND software was used to search the predicted amino acid sequences of each MAG against the UniProt TrEMBL database (ver. 2020-05, https://www.uniprot.org/statistics/TrEMBL) [51] with the parameter 'blastp' according to an e-value ≤1e−5. From the BLAST results for each sequence, the best BLAST hit was selected for subsequent analysis [52]. Sequences that could not be aligned were defined as unknown proteins. To understand the functions of the assembled MAG, we used DIAMOND software to compare the predicted proteins to the KEGG database (ver. 2018-01-01, http://www.kegg.jp/kegg/) to obtain KEGG orthologues to determine the functional pathways in which the MAG participated. All of the predicted proteins were searched against the CAZy database (ver. 201801, http://www.cazy.org/), using dbCAN2 [53] and HMMER (version 3.3.1) [54] to annotate CAZy. Based on these results, we counted the number of functional genes with nonzero abundances [29]. PUL were predicted for Bacteroidetes MAG by using PULpy software [27]. The sex and breed were regarded as environmental factors and used Mantel test analysis in the vegan package of R 4.0.4 to test the correlation between the cazy abundance matrix and the environmental factor matrix with default parameters [55]. Resistance Gene Identifier (RGI, version 5.1.0) software was used to align the predicted proteomes to CARD (version 3.0.8) with the parameter setting blastp [56, 57].
Faecal RNA extraction and real-time RT–PCR
Faecal total RNA was extracted from frozen tissues after grinding under liquid nitrogen using TRIzol (Invitrogen, CA, USA) according to the manufacturer's protocol. The quantity and purity of total RNAs were detected by using NanoDrop 2000 Spectrophotometer (Thermo Scientific, Wilmington, DE). The isolated RNA was employed to synthesize cDNA using an RT–PCR kit (Takara, Dalian, China). The RT Primer Mix (Mixture of Random 6 mers and Oligo dT Primer) included in the kit was used as the primer for RT–PCR. All real-time RT–PCR analyses were performed using TB Green (TaKaRa Biotech, Dalian) according to the manufacturer's protocol. All primer information is listed in Additional file 2: Table S2.
Mice treadmill experiment
Sixteen CL57BL/6 mice about 12 weeks old (±1 week) were purchased from the Experimental Animal Center of Huiji District, Zhengzhou City (Zhengzhou, Henan, China). All mice were housed in the Animal Genetic Engineering Laboratory at Shihezi University. C57BL/6J mice were housed in SPF individually ventilated cages (2 mice per cage) under the controlled room temperature (23°C ± 3°C) and relative humidity (60 ± 10%) conditions, with a reverse light to dark cycle (12:12). C57BL/6J mice were left to acclimate for 1 week and were randomly divided into two groups based on body weight. One group was treated with normal standard diets (Experimental Mice Maintenance Feed (AIN-93), XIETONG SHENGWU, Nanjing, China) containing 3.5% and 0.5% acetate and butyrate (Solarbio, Beijing, China), and the other group was supplemented with an equal amount of sodium chloride (Solarbio, Beijing, China) in the feed as a control. The processed diets were stored in a −20°C freezer, and the diets of all mice were changed daily at 10:00 am. Both groups of mice were given free access to water and diets. For 3 days before starting treatment, mice were acclimated daily to the treadmill (No. XR-PT-10B; Shanghai XinRuan Information Technology Co., Ltd. Shanghai, China) by walking at 10 m/min for 10 min. Exercise capacity was measured after 4 weeks of treatment as previously described [58, 59]. The inclination of the runway was 11°. The exercise regimen was started with shock grid ON at 10 m/min for 30 S; speed was increased by 1 m/3 min up to 20 m/min and then held at 20 m/min until exhaustion. The electric shock intensity was 2mA, and the electric shock tolerance time was 10 s. The exhaustion time of each mouse was recorded for analysis.
Statistical analysis and graphing
Phylogenetic trees were drawn with GraPhlAn ver. 1.1.3 [60] and the ggtree packages [61] in R ver. 3.6.2 or iTOL. All other statistical analyses were carried out in R ver. 3.6.2. The ComplexHeatmap package [62] was used to visualize all of the heatmaps. Box plots and scatter plots were drawn with the ggplot2 package [63]. Rarefaction analysis was performed to characterize gene richness. Our samples were randomly sampled 100 times with replacement, and the total number of genes that could be identified from these samples was estimated with R ver. 2.15.3 (vegan package) [64].
Results and discussion
Samples and metagenomic sequencing data
To provide a resource for studying the horse gut microbiome, metagenome sequencing was performed on 110 caecal and 132 rectal gut (faeces) samples from a total of 242 horses of different ages (range: 1–11 years), sexes (female, male), and breeds (Thoroughbred, Yili horse, Yili racehorse, Tibetan horse, or Shetland pony) and that were maintained under different diets (Additional file 1: Table S1, Fig. 1A). Using high-throughput sequencing, we obtained 2.267 Tb of Illumina sequencing data from all 242 samples. After quality control, a total of 2.264 Tb of clean, high-quality data remained, with an effective data quality control rate of 99.86% (Additional file 3: Table S3). To evaluate the total number of genes that could be identified from these samples, rarefaction analysis was performed with random sampling 100 times. The rarefaction curve was close to saturation (Additional file 4: Fig. S1), indicating that the sequence data were sufficient for a genomic analysis of the horse gut microbiota and that few novel genes had gone undetected. In addition, for improving the quality of data assembly, we sequenced two samples (HGM35 and HGM77) by using Nanopore sequencing and obtained 0.057 Tb of long-read sequencing data.
Assembly of 4142 microbial genomes from the horse gut
We used the metaWRAP-Binning module to generate 6408 bins (MaxBin2), 7495 bins (metaBAT2), and 12,415 bins (CONCOCT) (Fig. 1A, left side). After dereplication (average nucleotide identity (ANI) ≤99%) and quality assessment, we obtained a final set of 4099 MAG that met or exceeded the previously established medium-quality criteria (completeness ≥ 50% and contamination ≤ 10%; [65]). An additional 43 genomes were generated from the two sequenced samples (HGM35 and HGM77) via the Nanopore sequencing approach (Fig. 1A, right side). Thus, we assembled a total of 4142 MAG by using Illumina and Nanopore sequencing technologies (Additional file 5: Table S4). Among the 4142 MAG, 2272 were high-quality genomes (defined as > 80% completeness and < 10% contamination [66]) (Fig. 1B); 646 showed > 95% completeness and < 5% contamination; and 46 presented > 97% completeness and 0% contamination (Additional file 6: Fig. S2).
To classify the 4142 MAG, these MAG sequences were aligned with the Genome Taxonomy Database (GTDB). Further analysis showed that 126 of the 4142 MAG were identified at the species level, 3462 were identified at the genus level, 4127 were identified at the family level, 4139 were identified at the order level, and 4142 were identified at the class level. Clustering of MAG with ANI of 99% and 95% for strain-level and species-level genome bins threshold, respectively, we found that 3253 MAG could be considered species-level genomes. All 4142 MAG were classified into GTDB-predicted taxa (Fig. 1C), including 18 bacterial phyla (n = 4127 MAG) and 3 archaeal phyla (n = 15 MAG). As shown in Fig. 1C, the top 10 bacterial phyla were Bacteroidota (2065 MAG), Firmicutes (1432 MAG), Verrucomicrobiota (200 MAG), Spirochaetota (175 MAG), Fibrobacterota (75 MAG), Proteobacteria (70 MAG), Synergistota (23 MAG), Patescibacteria (64 MAG), Desulfobacterota (17 MAG), Elusimicrobiota (12 MAG), and Campylobacterota (11 MAG). 4015 of the 4142 MAG (> 96.93%) did not match the reference genomes in the GTDB and therefore represented unknown species or strains identified for the first time in this study (Additional file 7: Table S5). By dereplication with the horse MAG from previous studies [6, 20, 21] based on the 95% ANI level, we found that 3936 MAG were unique in this study (Additional file 8: Table S6). Upon comparing the MAG identified in 242 horses, we found that 36 core MAG were present in at least 90% of samples, including Bacteroidota (MAG = 16), Firmicutes (MAG = 18) and Verrucomicrobiota (MAG = 2) (Additional file 9: Table S7), and these phyla were also present in the reported horse gut metagenomic data [6, 67]. Meanwhile, MAG with a relative abundance of <1% in 90% of the samples were considered rare [68], and a total of 43 MAG were identified as rare (Additional file 10: Table S8).
Among the 15 archaeal MAG obtained in this study, 13 belonged to unknown species. All archaeal MAG were assigned to three phyla: Halobacterota (n = 9), Thermoplasmatota (n = 4), and Euryarchaeota (n = 2). To reveal the potential functions of the archaeal MAG, 6 high-quality archaeal MAG were chosen based on >80% completeness threshold and were further analysed for the presence of methanogenic pathway genes involved in methane production. All 6 high-quality archaeal MAG contained >500 methanogenic genes (Additional file 11: Table S9). Interestingly, MAG23.bin.19 (100% completeness and 0% contamination) contained the most methanogenic genes identified among these archaeal MAG and could utilize all three known pathways (hydrogenotrophic, acetoclastic, and methylotrophic pathways) to produce methane (Additional file 11: Table S9). MAG23.bin.19 was assigned to Methanobrevibacter smithii. Previous study reported that Methanobrevibacter smithii was the dominant archaeon (representing up to 10% of all anaerobes) in the gut of humans and promoted the production of methane in the human large intestine [69]. Meanwhile, Methanobrevibacter smithii is also an important methanogen in the rumen [70]. Together, our results suggest that MAG23.bin.19 may be a major contributor to methane production in horses. The complete genome information of Methanobrevibacter smithii may provide novel targets for mitigating methane production, although further experimental analysis is needed to confirm this in the future.
Assembling the first complete, circularized genomes of 13 unknown species from long-read data
To generate complete microbial genomes, two metagenomic samples (HGM35, female; HGM77, male) were subjected to Nanopore sequencing, which produced more than 50.13 Gb of clean data (more than 57.71 Gb of raw data at an efficiency of > 86.85%). The average read length was 55,063 bp, which is superior to the data reported in previous studies [27, 71]. After assembling these long reads, we obtained a sequence that was 739 Mb long, and the N50 value reached 217 kb. As shown in the pipeline diagram (Fig. 1A), we assembled 32 new high-quality MAG that had not previously been identified in public databases. Compared with Illumina data, we observed that Nanopore sequencing data was superior in assembly length and contig length (Fig. 2A, Additional file 5: Table S4).
Long reads can be used to assemble near-complete circular MAG (cMAG) from a single scaffold, which greatly improves the accuracy of the assembly. Among the 32 MAG generated from long reads, 13 were successfully assembled into cMAG, which is an important achievement of long-read assembly (Additional file 12: Table S10). The average completeness and contamination of these cMAG were 93.25% and less than 0.99%, respectively. The cumulative GC skew and genomic GC content were used to verify the assembly quality of the cMAG (Additional file 13: Fig. S3).
These 13 cMAG were further compared with the NR database and the Genome Taxonomy Database Toolkit (GTDB-Tk) to identify homologous species. Among these homologous species, the highest ANI with cMAG was 83.69%. This relatively low ANI indicated the novelty of these cMAG representing the first circularized, complete genomes for respective species. These cMAG contained complete bacterial genome information, including multiple copies of 16S, 5S, and 23S rRNA operons and tRNA operons (Additional file 14: Table S11). We next identified the assembled genomes of the highest quality for further analysis based on contamination and selected MAG77.2830532.NO.32, MAG77.2876332.NO.18, and MAG77.3034135.NO.12, all of which had contamination scores of 0% (Fig. 2B, Additional file 13: Fig. S3, Additional file 12: Table S10). Comparisons with public databases identified MAG77.2830532.NO.32 as Anaerovibrio lipolyticus (ANI < 73.90%) and MAG77.2876332.NO.18 as a novel species of Ruminococcaceae bacteria (ANI < 71.20%) (Fig. 2B), and MAG77.3034135.NO.12 was identified as an unknown Ruminococcus sp. (ANI < 79.17%) [72]. We also searched for full-length 16S sequences in these genomes by comparison against the NCBI database, and the top hits were an uncultured rumen Anaerovibrio sp. (97.30% identity), uncultured Ruminococcus sp. (95.60% identity), and uncultured Ruminococcaceae bacterium (97.30% identity). According to the general standard for 16S rRNA-based taxonomy [73], only MAG77.2876332.NO.18 could be considered a new species, which further suggests the accuracy of the genome sequencing of the microbial taxa. These results suggest that the long-read assembly of MAG not only increased the integrity of the genome assemblies but also revealed previously unresolved genomic features and taxonomic information.
Hundreds of thousands of novel CAZy
Next, we analysed the proteomic contents and functions of the horse metagenomes by searching against the KEGG and CAZy databases [74, 75]. The 2272 high-quality MAG contained a total of 4,632,123 predicted proteins. By comparing gene catalogue of this study with that of published horse data reported by Mach et al., Youngblut et al., and Gilroy et al. [6, 20, 67], we found that our data greatly expanded the catalogue of equine gut microbial gene catalogue (Additional file 15: Fig. S4). Among the 4,632,123 predicted proteins, 6.77% (313,568) of which were predicted to have at least one CAZy function (Additional file 16: Table S12). The 313,568 CAZy proteins included 130,001 glycosyl hydrolases (GH), 73,365 glycosyl transferases (GT), 52,961 carbohydrate-binding modules (CBM), 46,437 carboxyesterases (CE), 6320 polysaccharide lyases (PL), and 4484 proteins with auxiliary activity (AA) (Fig. 3A; Additional file 17: Table S13). These proteins were unevenly distributed in the genomes of the taxa that we identified. For example, GH and GT were particularly enriched in Verrucomicrobiota and Firmicutes (Fig. 3B). We further analyse the similarity of the predicted CAZymes against the current CAZy database [27]. Among the 313,568 CAZy proteins, only 126,139 (40.23%) showed highly similar matches with ≥ 95% consistency, indicating that 187,429 of our predicted proteins were novel CAZy (Fig. 3C, Additional file 17: Table S13). Among all the classes of the predicted CAZymes, GH presented the greatest amino acid-level sequence identity (87.72%) with the CAZy in public databases, while AA presented the lowest identity of only 49.18% (Fig. 3C), indicating that a large portion of the diversity of CAZymes is missing from public databases.
We compared the CAZyme profiles of this study with those of prior horse study which was recently made available by Mach et al. [6], Youngblut et al. [20], and Gilroy et al. [67]. We found that our data significantly expand the number of CAZy in the horse gut (Fig. 3D). For these six classes of CAZy, including GT, GH, AA, PL, CE, and CBM, our data expanded the number of CAZy by at least an order of magnitude in the horse gut, although inconsistencies between our study and the prior study related to sample collection or sequencing method that may impact comparisons between these datasets. We further analyse the effect of horse gender or breeds on CAZyme profiles. CAZy gene abundance in the horse gut was significantly associated with sex (R2 = 0.04, P = 0.032) and breed (R2 = 0.2107, P = 0.001).
In addition, we detected 4492 polysaccharide utilization loci (PUL) among 556 Bacteroides species (Additional file 18: Table S14), which can degrade a variety of carbohydrate substrates in animal digestive systems [76]. Most of the 556 Bacteroides genomes had at least one PUL; Bacteroides fragilis (MAG117.bin.13), in particular, contained up to 48 PUL. In total, the identification of these novel CAZy and potentially cellulose-degrading bacteria will facilitate a better understanding of carbohydrate metabolism in horse gut and provide a rich source of novel enzymes and microbes for fermentation biotechnology industries [77, 78].
The horse gut as a reservoir of antibiotic resistance genes
To characterize horse intestinal antibiotic resistance genes (ARG), we examined the distribution of ARG in 2272 high-quality MAG among 242 horse gut samples. We identified a total of 266 unique types of ARG across 25 drug resistance classes in the horse gut MAG (Fig. 4A). The number of both ARG and drug resistance classes are fewer than those reported in pig and bovine gut [79, 80], which may be related to genetics, diet, and exposure to antibiotics in life. Firmicutes and Bacteroidota were the bacterial groups with the greatest numbers of ARG, and we also predicted ARG in three archaeal taxa, including Euryarchaeota and Halobacterota (Fig. 4A, Additional file 19: Table S15). Aminoglycoside, aminocoumarin, and tetracycline ARG were prevalent in the intestines of horses (Fig. 4A, Additional file 19: Table S15), which was consistent with previous ARG studies in the gut microbes of cattle, sheep, pig, chicken, and horses [20, 81, 82]. However, the aminoglycoside resistance genes were the most abundant ARG in the intestines of horses. The high abundance of aminoglycoside resistance genes has a potential negative impact on horse health given that aminoglycoside was widely used to treat respiratory diseases, septic peritonitis, acute febrile diarrhoea, and cellulitis in horses [83, 84].
Furthermore, a total of 2194 MAG (96.57%) contained five or more ARG (Additional file 20: Table S16), suggesting that ARG are widespread in the horse gut microbiome. We verified the transcriptional activity of these ARG by real-time RT-PCR using 10 randomly chosen ARG, and the results indicated that these predicted genes have real drug resistance functions (Fig. 4B, Additional file 21: Fig. S5). Surprisingly, an Escherichia coli strain (MAG166.bin.2) was found to contain 82 unique types of ARG belonging to 13 drug resistance classes (Fig. 4C, Additional file 20: Table S16). The strain contained a variety of resistance genes against fluoroquinolone antibiotics, cephalosporins, acridine dyes, carbapenems, aminoglycoside antibiotics, peptide antibiotics, and tetracycline antibiotics commonly used in livestock production. Considering the common pathogenicity of E. coli, this finding suggests that this strain may be a potential drug-resistant superbug. In addition, we found a large number of ARG in MAG49.bin.28 (Roseburia), MAG250.bin.22 (Prevotella), and MAG77.2754209.NO.29 (Akkermansia), members of which are widely reported to have probiotic effects [85,86,87] (Additional file 20: Table S16). Although antibiotic resistance could be used for facilitating the future isolation and culture of these strains, we may also consider the potential harm caused by these ARG to the host gut microbiome.
Then, the pair-wise comparisons of ARG prevalence in the gut of six populations (Yili horses, Thoroughbred, Shetland ponies, Tibetan horses, Yili nonracehorses, and Yili racehorses) were performed. Although the Yili horses had the largest sample size, the number and abundance of ARG in the Yili horses were not the largest. However, Thoroughbred horses had the highest abundance and number of ARG, which was more than two-fold times than that of Tibetan horses (Fig. 4D, E, Additional file 22: Table S17). Tibetan horses have the lowest abundance and number of ARG in the gut, and the horses graze freely on the Qinghai-Tibet Plateau with rare exposure to antibiotics. In addition, although genetic backgrounds, training patterns, and breeding sites of Yili racehorses, Yili horses, and Shetland ponies were different, the abundance and quantity of ARG in the guts of these horses were similar. Among these six breeds, Thoroughbred horses are subjected to commercially formulated feeds, antibiotic administration, stabling, and confinement conditions throughout the life cycle, which may be one of the reasons for the high antibiotic abundance of ARG in Thoroughbred populations [79].
Novel insights into potential performance-enhancing microbes in racehorses
To reveal the link between the gut microbiota and exercise performance in racehorses, we examined the differences between the microbiomes of elite racehorses (n = 21, Yili racehorses) and a group of age-matched nonracehorses horses (n = 35, Yili horses). Principal coordinate analysis (PCoA) revealed that the microbial compositions of the racehorses and nonracehorses were distinctly separated (Fig. 5A). Further analysis of the differences in the composition of the gut microbiomes of the two groups at the species level was performed. The MAG from Prevotella (MAG36.bin.6, MAG266.bin.12, MAG146.bin.68, MAG122.bin.6, MAG120.bin.60) [88], Lachnospiraceae (MAG252.bin.16, MAG32.bin.44) [89], Phascolarctobacterium (MAG20.bin.3, MAG19.bin.10, MAG23.bin.66, MAG3.bin.34, MAG58.bin.49, MAG23.bin.2, MAG35.bin.4, MAG80.bin.33, MAG240.bin.26, MAG77.bin.65, MAG104.bin.14, MAG148.bin.27) [90], Oscillospiraceae (MAG59.bin.38) [91], Eubacterium (MAG77.bin.21) [92], and Ruminococcus (MAG73.bin.20, MAG28.bin.65) [93] showed higher abundances in the guts of elite racehorses than in those of nonracehorses (Fig. 5B, Additional file 23: Table S18). Lachnospiraceae and Ruminococcus were the highly abundant microbes in racehorse, which is in agreement with a study in endurance horses by Plancade et al. [14]. Interestingly, Lachnospiraceae, Oscillospiraceae, and Ruminococcus, defined as performance-associated bacteria, have been found to be enriched in the microbiomes of human athletes, suggesting that the performance-associated bacteria may be, at least in part, conserved across animals and human [94].
To further explore the functions of the differentially abundant bacteria, we compared the metabolic pathways of the microbiome between the racehorses group and nonracehorses group. As shown in Fig. 5C, Lachnospiraceae, Phascolarctobacterium, Oscillospiraceae, Eubacterium, Ruminococcus, Campylobacteraceae, Methanobacteriaceae, Succinivibrionaceae, Bacteroidaceae, Erysipelotrichaceae, and Treponemataceae, which were enriched in the racehorses (Fig. 5B, Additional file 23: Table S18), contained many key enzymes in the acetate and butyrate synthesis pathways. The key enzymes (EC 188.8.131.52, EC 18.104.22.168, EC 18.104.22.168, EC220.127.116.11, EC 18.104.22.168, EC 184.108.40.206, EC 220.127.116.11, EC 22.214.171.124, and EC 22.214.171.124) in the acetate and butyrate synthesis pathways were significantly enriched in the racehorses gut when compared with nonracehorses (Fig. 5D). More importantly, 36 MAG (e.g. MAG15.bin.4 belonging to Lachnospiraceae, MAG122.bin.15 belonging to Oscillospiraceae, MAG28.bin.65 belonging to Ruminococcus, and MAG17.bin.19 belonging to Treponema) were higher in racehorses than that in nonracehorses (Additional file 24: Fig. S6). The enrichment of Treponema in racehorses is consistent with previous studies performed in endurance horses by Plancade et al. [14] and in Standardbred racehorses by Janabi et al. [19] that showed that training led to an increase in Treponema. These MAG enriched in Yili racehorses contained every gene in a major pathway for producing acetate and butyrate (Additional file 24: Fig. S6). These results suggest these microbes enriched in the racehorses may synthesize more acetate and butyrate in the gut. However, the differences observed here were likely due to the different diets, environment, or exercise of racehorses and nonracehorses. Future studies is needed to confirm this.
Acetate and butyrate have been shown to modulate skeletal muscle function and exercise capacity [93, 95,96,97]. Several groups have reported that continuous supplementation of acetate alone or together with butyrate improves endurance performance and muscular strength [98, 99]. We also confirmed that infusion of the SCFA (a mixture of acetate and butyrate) into mice resulted in significant increase of maximum time to exhaustion (Fig. 5E). Mice treated with oral SCFA infusion, on average, showed approximately 87.23% increase in run times when compared with the saline vehicle group (n = 8). Although it has been reported that oral acetic acid can serve as an important energy source for skeletal muscle at rest in horses [95, 96], whether or not SCFA can enhance athletic performance in horses needs to be in-depth studied in the future.
We present the large-scale metagenomic sequencing dataset and reference genome assembly for the horse gut microbiome, which will improve the ability to perform taxonomic grouping and metagenomic and metatranscriptomic analyses for future microbiome studies of horses. High abundance and diversity of ARG were identified in the MAG, which showed the horse gut as a reservoir of antibiotic resistance genes. In addition, by using the assembled genome to mine the functions of the horse gut microbiome, 36 MAG (e.g. belonging to Lachnospiraceae, Oscillospiraceae, and Ruminococcus) was observed to be enriched in the racehorses. These bacteria enriched in racehorses may produce more acetate and butyrate, presenting potential for greater amount of short-chain fatty acids available to fuel athletic performance. These acetate and butyrate-producing microbes are expected to be used as biomarkers for identifying or selecting endurance racehorses and may be developed into probiotics that are used for promoting horse exercise and health in the future. Our study provides exhaustive reference genomic datasets for the horse gut microbiota, and our results emphasize the complex interactions between the host and the gut microbiota.
Availability of data and materials
All of the original sequences obtained in this work have been deposited in the National Center for Biotechnology Information (NCBI) under project number PRJEB871798. The MAG sequences, the gene catalogue, and source code are available at Zenodo (https://doi.org/10.5281/zenodo.7240014). All of the data can also be obtained from the corresponding author upon reasonable request or from the included supplementary information files.
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Not applicable.
This work was supported financially by the Third Xinjiang Scientific Expedition Program [2021xjkk0605 and 2021xjkk0504] and the Foundation of State Key Laboratories for Sheep Genetic Improvement and Healthy Production [2021ZD08].
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Authors and Affiliations
W.N., C.L., and S.H. conceived and coordinated the project. K.L., Z.L., J.D., Y.X., S.A., Z.W., Y.Z., B.L., Y.Z., Y.W., W.Z., Q.Z., C.C., and J.Q. performed the collection of samples. C.L. and X.L. performed the metagenomic sequencing. C.L., X.L., and R.G. performed the analysis of the metagenomic sequences prior to binning, as well as prokaryotic binning. C.L., X.L., and R.G. carried out the bacteria binning. Analysis of MAG was performed by W.N., C.L., S.H., C.L., X.L., and R.G. and they participated in the manuscript writing and revision. W.N., C.L., and S.H. supervised the study. All authors approved the final version of the manuscript.
Corresponding authors
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Ethics approval and consent to participate
All of the procedures involving animals were approved by the Animal Care Committee of Shihezi University. The study was performed in accordance with the ethical standards established in the 1964 Declaration of Helsinki and subsequent amendments.
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The authors declare that they have no competing interests.
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Supplementary Information
Additional file 1: Table S1.
All detailed information on experimental horses and samples.
Additional file 2: Table S2.
Details of the primers of the 10 ARG used for real-time PCR.
Additional file 3: Table S3.
Statistics and quality control information for the sequence data.
Additional file 4: Figure S1.
Rarefaction curve of the gene numbers in our samples. The curve nearly plateaus when sufficient sequence data are included, with few novel genes being left undetected.
Additional file 5: Table S4.
Information on 4142 MAG obtained from the gut of horse using Illumina and Nanopore sequencing technologies.
Additional file 6: Figure S2.
Assessment of the degree of contamination and integrity of 2272 high-quality MAG in the horse gut. The grey circles indicate 80–90% genome integrity with 5–10% contamination; the red circles indicate > 90% genome integrity with < 5% contamination.
Additional file 7: Table S5.
Comparison of 4142 MAG with the public database.
Additional file 8: Table S6.
Check the uniqueness of the MAG in this study by deduplicating the MAG reported in previous studies.
Additional file 9: Table S7.
Detailed description of the 36 core MAG. Core MAG were present in at least 90% samples.
Additional file 10: Table S8.
Abundance of 4142 MAG in 242 samples.
Additional file 11: Table S9.
All 6 archaeal MAG contained hundreds of methanogenic genes.
Additional file 12: Table S10.
Details of the MAG assembled by Nanopore sequencing that are expected to be circular contigs.
Additional file 13: Figure S3.
Overview of 11 circular genomes. From the outside to the inside, the concentric circles indicate the positional coordinates of the genomic sequence, coding genes, gene annotation, noncoding RNAs, genomic GC content, and genomic GC skew values. Gene annotation: different colours are used to distinguish different terms of the KEGG and GO annotations. Genome GC content: the inner, red part indicates that the GC content of the region is less than the average GC content of the whole genome; the outer, green part indicates that the GC content of the region is greater than the average value. GC skew value: the inner, pink part indicates that the G content in the area is less than the C content; the outer, light-green part indicates that the G content in the area is greater than the C content.
Additional file 14: Table S11.
16S rRNA gene data in the complete genomes assembled by Nanopore sequencing.
Additional file 15: Figure S4.
Venn plots of the gene catalogues of this study and previous published horse study. Data for published articles are marked with author names.
Additional file 16: Table S12.
Analysis of proteins functions for the 2272 MAG.
Additional file 17: Table S13.
Detailed information on the six active polysaccharide-degrading enzymes (GH, GT, PL, CE, CBM, and AA) among the proteins encoded by the 2272 genomes.
Additional file 18: Table S14.
Details of 4492 PUL contained in 556 Bacteroides MAG.
Additional file 19: Table S15.
ARG encoded by horse intestinal MAG were identified into 25 resistance classes.
Additional file 20: Table S16.
266 ARG predicted in 2272 MAG.
Additional file 21: Figure S5.
RT–PCR amplification of 10 randomly selected ARG. M is the size marker (Takara DL500: 500 bp, 400 bp, 300 bp, 200 bp, 150 bp, 100 bp, and 50 bp), and N is the negative control.
Additional file 22: Table S17.
Abundance of antibiotic resistance genes in 242 samples.
Additional file 23: Table S18.
The differences of microbial composition in racehorses and nonracehorses.
Additional file 24: Figure S6.
The racehorse gut is rich in microbes that can synthesize acetate and butyrate. The microbes enriched in racehorses contain a large number of enzymes that synthesize acetate and butyrate. At the bottom of the heatmap are the difference MAG ID, and the top are the taxonomic information of the MAG.
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Li, C., Li, X., Guo, R. et al. Expanded catalogue of metagenome-assembled genomes reveals resistome characteristics and athletic performance-associated microbes in horse. Microbiome 11, 7 (2023). https://doi.org/10.1186/s40168-022-01448-z
DOI: https://doi.org/10.1186/s40168-022-01448-z


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