The camel is well-adapted to utilize the poor-quality forages in the harsh desert conditions as the camel rumen sustains fibrolytic microorganisms, mainly bacteria that are capable of breaking down the lignocellulosic biomass efficiently. Exploring the composition of the bacterial community in the rumen of the camel and quantifying their cellulolytic and xylanolytic activities could lead to understanding and improving fiber fermentation and discovering novel sources of cellulases and xylanases. In this study, Illumina MiSeq sequencing of the V4 region on 16S rRNA was applied to identify the bacterial and archaeal communities in the rumen of three camels fed wheat straw and broom corn. Furthermore, rumen samples were inoculated into bacterial media enriched with xylan and different cellulose sources, including filter paper (FP), wheat straw (WS), and alfalfa hay (AH) to assess the ability of rumen bacteria to produce endo-cellulase and endo-xylanase at different fermentation intervals. The results revealed that the phylum Bacteroidetes dominated the bacterial community and Candidatus Methanomethylophilus dominated the archaeal community. Also, most of the bacterial community has fibrolytic potential and the dominant bacterial genera were Prevotella, RC9_gut_group, Butyrivibrio, Ruminococcus, Fibrobacteres, and Treponema. The highest xylanase production (884.8 mU/mL) was observed at 7 days. The highest cellulase production (1049.5 mU/mL) was observed when rumen samples were incubated with Alfalfa hay for 7 days.
Citation: Alaa Emara Rabee, Robert Forster, Ebrahim A Sabra. Lignocelluloytic activities and composition of bacterial community in the camel rumen[J]. AIMS Microbiology, 2021, 7(3): 354-367. doi: 10.3934/microbiol.2021022
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The camel is well-adapted to utilize the poor-quality forages in the harsh desert conditions as the camel rumen sustains fibrolytic microorganisms, mainly bacteria that are capable of breaking down the lignocellulosic biomass efficiently. Exploring the composition of the bacterial community in the rumen of the camel and quantifying their cellulolytic and xylanolytic activities could lead to understanding and improving fiber fermentation and discovering novel sources of cellulases and xylanases. In this study, Illumina MiSeq sequencing of the V4 region on 16S rRNA was applied to identify the bacterial and archaeal communities in the rumen of three camels fed wheat straw and broom corn. Furthermore, rumen samples were inoculated into bacterial media enriched with xylan and different cellulose sources, including filter paper (FP), wheat straw (WS), and alfalfa hay (AH) to assess the ability of rumen bacteria to produce endo-cellulase and endo-xylanase at different fermentation intervals. The results revealed that the phylum Bacteroidetes dominated the bacterial community and Candidatus Methanomethylophilus dominated the archaeal community. Also, most of the bacterial community has fibrolytic potential and the dominant bacterial genera were Prevotella, RC9_gut_group, Butyrivibrio, Ruminococcus, Fibrobacteres, and Treponema. The highest xylanase production (884.8 mU/mL) was observed at 7 days. The highest cellulase production (1049.5 mU/mL) was observed when rumen samples were incubated with Alfalfa hay for 7 days.
In this paper, we consider the Schrödinger operators
L=−△+V(x),x∈Rn,n≥3, |
where Δ=∑ni=1∂2∂2xi and V(x) is a nonnegative potential belonging to the reverse Hölder class RHq for some q≥n2. Assume that f is a nonnegative locally Lq(Rn) integrable function on Rn, then we say that f belongs to RHq (1<q≤∞) if there exists a positive constant C such that the reverse Hölder's inequality
(1|B(x,r)|∫B(x,r)|f(y)|qdy)1q≤C|B(x,r)|∫B(x,r)|f(y)|dy |
holds for x in Rn, where B(x,r) denotes the ball centered at x with radius r<∞ [1]. For example, the nonnegative polynomial V∈RH∞, in particular, |x|2∈RH∞.
Let the potential V∈RHq with q≥n2, and the critical radius function ρ(x) is defined as
ρ(x)=supr>0{r:1rn−2∫B(x,r)V(y)dy≤1},x∈Rn. | (1.1) |
We also write ρ(x)=1mV(x),x∈Rn. Clearly, 0<mV(x)<∞ when V≠0, and mV(x)=1 when V=1. For the harmonic oscillator operator (Hermite operator) H=−Δ+|x|2, we have mV(x)∼(1+|x|).
Thanks to the heat diffusion semigroup e−tL for enough good function f, the negative powers L−α2(α>0) related to the Schrödinger operators L can be written as
Iαf(x)=L−α2f(x)=∫∞0e−tLf(x)tα2−1dt,0<α<n. | (1.2) |
Applying Lemma 3.3 in [2] for enough good function f holds that
Iαf(x)=∫RnKα(x,y)f(y)dy,0<α<n, |
and the kernel Kα(x,y) satisfies the following inequality
Kα(x,y)≤Ck(1+|x−y|(mV(x)+mV(y)))k1|x−y|n−α. | (1.3) |
Moreover, we have Kα(x,y)≤C|x−y|n−α,0<α<n.
Shen [1] obtained Lp estimates of the Schrödinger type operators when the potential V∈RHq with q≥n2. For Schrödinger operators L=−Δ+V with V∈RHq for some q≥n2, Harboure et al. [3] established the necessary and sufficient conditions to ensure that the operators L−α2(α>0) are bounded from weighted strong and weak Lp spaces into suitable weighted BMOL(w) space and Lipschitz spaces when p≥nα. Bongioanni Harboure and Salinas proved that the fractional integral operator L−α/2 is bounded form Lp,∞(w) into BMOβL(w) under suitable conditions for weighted w [4]. For more backgrounds and recent progress, we refer to [5,6,7] and references therein.
Ramseyer, Salinas and Viviani in [8] studied the fractional integral operator and obtained the boundedness from strong and weak Lp(⋅) spaces into the suitable Lipschitz spaces under some conditions on p(⋅). In this article, our main interest lies in considering the properties of fractional integrals operator L−α2(α>0), related to L=−Δ+V with V∈RHq for some q≥n2 in variable exponential spaces.
We now introduce some basic properties of variable exponent Lebsegue spaces, which are used frequently later on.
Let p(⋅):Ω→[1,∞) be a measurable function. For a measurable function f on Rn, the variable exponent Lebesgue space Lp(⋅)(Ω) is defined by
Lp(⋅)(Ω)={f:∫Ω|f(x)s|p(x)dx<∞}, |
where s is a positive constant. Then Lp(⋅)(Ω) is a Banach space equipped with the follow norm
‖f‖Lp(⋅)(Ω):=inf{s>0:∫Ω|f(x)s|p(x)dx≤1}. |
We denote
p−:=essinfx∈Ωp(x) and p+:=esssupx∈Ωp(x). |
Let P(Rn) denote the set of all measurable functions p on Rn that take value in [1,∞), such that 1<p−(Rn)≤p(⋅)≤p+(Rn)<∞.
Assume that p is a real value measurable function p on Rn. We say that p is locally log-Hölder continuous if there exists a constant C such that
|p(x)−p(y)|≤Clog(e+1/|x−y|),x,y∈Rn, |
and we say p is log-Hölder continuous at infinity if there exists a positive constant C such that
|p(x)−p(∞)|≤Clog(e+|x|),x∈Rn, |
where p(∞):=lim|x|→∞p(x)∈R.
The notation Plog(Rn) denotes all measurable functions p in P(Rn), which states p is locally log-Hölder continuous and log-Hölder continuous at infinity. Moreover, we have that p(⋅)∈Plog(Rn), which implies that p′(⋅)∈Plog(Rn).
Definition 1.1. [8] Assume that p(⋅) is an exponent function on Rn. We say that a measurable function f belongs to Lp(⋅),∞(Rn), if there exists a constant C such that for t>0,
∫Rntp(x)χ{|f|>t}(x)dx≤C. |
It is easy to check that Lp(⋅),∞(Rn) is a quasi-norm space equipped with the following quasi-norm
‖f‖p(⋅),∞=inf{s>0:supt>0∫Rn(ts)p(x)χ{|f|>t}(x)dx≤1}. |
Next, we define LipLα,p(⋅) spaces related to the nonnegative potential V.
Definition 1.2. Let p(⋅) be an exponent function with 1<p−≤p+<∞ and 0<α<n. We say that a locally integrable function f∈LipLα,p(⋅)(Rn) if there exist constants C1,C2 such that for every ball B⊂Rn,
1|B|αn‖χB‖p′(⋅)∫B|f(x)−mBf|dx≤C1, | (1.4) |
and for R≥ρ(x),
1|B|αn‖χB‖p′(⋅)∫B|f(x)|dx≤C2, | (1.5) |
where mBf=1|B|∫Bf. The norm of space LipLα,p(⋅)(Rn) is defined as the maximum value of two infimum of constants C1 and C2 in (1.4) and (1.5).
Remark 1.1. LipLα,p(⋅)(Rn)⊂Lα,p(⋅)(Rn) is introduced in [8]. In particular, when p(⋅)=C for some constant, then LipLα,p(⋅)(Rn) is the usual weighted BMO space BMOβL(w), with w=1 and β=α−np [4].
Remark 1.2. It is easy to see that for some ball B, the inequality (1.5) leads to inequality (1.4) holding, and the average mBf in (1.4) can be replaced by a constant c in following sense
12‖f‖LipLα,p(⋅)≤supB∈Rninfc∈R1|B|αn‖χB‖p′(⋅)∫B|f(x)−c|dx≤‖f‖LipLα,p(⋅). |
In 2013, Ramseyer et al. in [8] studied the Lipschitz-type smoothness of fractional integral operators Iα on variable exponent spaces when p+>αn. Hence, when p+>αn, it will be an interesting problem to see whether or not we can establish the boundedness of fractional integral operators L−α2(α>0) related to Schrödinger operators from Lebesgue spaces Lp(⋅) into Lipschitz-type spaces with variable exponents. The main aim of this article is to answer the problem above.
We now state our results as the following two theorems.
Theorem 1.3. Let potential V∈RHq for some q≥n/2 and p(⋅)∈Plog(Rn). Assume that 1<p−≤p+<n(α−δ0)+ where δ0=min{1,2−n/q}, then the fractional integral operator Iα defined in (1.2) is bounded from Lp(⋅)(Rn) into LipLα,p(⋅)(Rn).
Theorem 1.4. Let the potential V∈RHq with q≥n/2 and p(⋅)∈Plog(Rn). Assume that 1<p−≤p+<n(α−δ0)+ where δ0=min{1,2−n/q}. If there exists a positive number r0 such that p(x)≤p∞ when |x|>r0, then the fractional integral operator Iα defined in (1.2) is bounded from Lp(⋅),∞(Rn) into LipLα,p(⋅)(Rn).
To prove Theorem 1.3, we first need to decompose Rn into the union of some disjoint ball B(xk,ρ(xk))(k≥1) according to the critical radius function ρ(x) defined in (1.1). According to Lemma 2.6, we establish the necessary and sufficient conditions to ensure f∈LipLα,p(⋅)(Rn). In order to prove Theorem 1.3, by applying Corollary 1 and Remark 1.2, we only need to prove that the following two conditions hold:
(ⅰ) For every ball B=B(x0,r) with r<ρ(x0), then
∫B|Iαf(x)−c|dx≤C|B|αn‖χB‖p′(⋅)‖f‖p(⋅); |
(ⅱ) For any x0∈Rn, then
∫B(x0,ρ(x0))Iα(|f|)(x)dx≤C|B(x0,ρ(x0))|αn‖χB(x0,ρ(x0))‖p′(⋅)‖f‖p(⋅). |
In order to check the conditions (ⅰ) and (ⅱ) above, we need to find the accurate estimate of kernel Kα(x,y) of fractional integral operator Iα (see Lemmas 2.8 and 2.9, then use them to obtain the proof of this theorem; the proof of the Theorem 1.4 proceeds identically).
The paper is organized as follows. In Section 2, we give some important lemmas. In Section 3, we are devoted to proving Theorems 1.3 and 1.4.
Throughout this article, C always means a positive constant independent of the main parameters, which may not be the same in each occurrence. B(x,r)={y∈Rn:|x−y|<r}, Bk=B(x0,2kR) and χBk are the characteristic functions of the set Bk for k∈Z. |S| denotes the Lebesgue measure of S. f∼g means C−1g≤f≤Cg.
In this section, we give several useful lemmas that are used frequently later on.
Lemma 2.1. [9] Assume that the exponent function p(⋅)∈P(Rn). If f∈Lp(⋅)(Rn) and g∈Lp′(⋅)(Rn), then
∫Rn|f(x)g(x)|dx≤rp‖f‖Lp(⋅)(Rn)‖g‖Lp′(⋅)(Rn), |
where rp=1+1/p−−1/p+.
Lemma 2.2. [8] Assume that p(⋅)∈Plog(Rn) and 1<p−≤p+<∞, and p(x)≤p(∞) when |x|>r0>1. For every ball B and f∈Lp(⋅),∞ we have
∫B|f(x)|dx≤C‖f‖Lp(⋅),∞‖χB‖Lp′(⋅), |
where the constant C only depends on r0.
Fo the following lemma see Corollary 4.5.9 in [10].
Lemma 2.3. Let p(⋅)∈Plog(Rn), then for every ball B⊂Rn we have
‖χB‖p(⋅)∼|B|1p(x),if|B|≤2n,x∈B, |
and
‖χB‖p(⋅)∼|B|1p(∞),if|B|≥1. |
Lemma 2.4. Assume that p(⋅)∈Plog(Rn), then for all balls B and all measurable subsets S:=B(x0,r0)⊂B:=B(x1,r1) we have
‖χS‖p′(⋅)‖χB‖p′(⋅)≤C(|S||B|)1−1p−, ‖χB‖p′(⋅)‖χS‖p′(⋅)≤C(|B||S|)1−1p+. | (2.1) |
Proof. We only prove the first inequality in (2.1), and the second inequality in (2.1) proceeds identically. We consider three cases below by applying Lemma 2.3, and it holds that
1) if |S|<1<|B|, then ‖χS‖p′(⋅)‖χB‖p′(⋅)∼|S|1p′(xS)|B|1p′(∞)≤(|S||B|)1(p′)+=(|S||B|)1−1p−;
2) if 1≤|S|<|B|, then ‖χS‖p′(⋅)‖χB‖p′(⋅)∼|S|1p′(∞)|B|1p′(∞)≤(|S||B|)1(p′)+=(|S||B|)1−1p−;
3) if |S|<|B|<1, then ‖χS‖p′(⋅)‖χB‖p′(⋅)∼|S|1p′(xS)|B|1p′(xS)|B|1p′(xS)−1p′(xB)≤C(|S||B|)1(p′)+=C(|S||B|)1−1p−, where xS∈S and xB∈B.
Indeed, since |xB−xS|≤2r1, by using the local-Hölder continuity of p′(x) we have
|1p′(xS)−1p′(xB)|log1r1≤log1r1log(e+1|xS−xB|)≤log1r1log(e+12r1)≤C. |
We end the proof of this lemma.
Remark 2.1. Thanks to the second inequality in (2.1), it is easy to prove that
‖χ2B‖p′(⋅)≤C‖χB‖p′(⋅). |
Lemma 2.5. [1] Suppose that the potential V∈Bq with q≥n/2, then there exists positive constants C and k0 such that
1) ρ(x)∼ρ(y) when |x−y|≤Cρ(x);
2) C−1ρ(x)(1+|x−y|ρ(x))−k0≤ρ(y)≤Cρ(x)(1+|x−y|ρ(x))k0/(k0+1).
Lemma 2.6. [11] There exists a sequence of points {xk}∞k=1 in Rn such that Bk:=B(xk,ρ(xk)) satisfies
1) Rn=⋃kBk,
2) For every k≥1, then there exists N≥1 such that card {j:4Bj∩4Bk≠∅}≤N.
Lemma 2.7. Assume that p(⋅)∈P(Rn) and 0<α<n. Let sequence {xk}∞k=1 satisfy the propositions of Lemma 2.6. Then a function f∈LipLα,p(⋅)(Rn) if and only if f satisfies (1.4) for every ball, and
1|B(xk,ρ(xk))|αn‖χB(xk,ρ(xk))‖p′(⋅)∫B(xk,ρ(xk))|f(x)|dx≤C,forallk≥1. | (2.2) |
Proof. Let B:=B(x,R) denote a ball with center x and radius R>ρ(x). Noting that f satisfies (1.4), and thanks to Lemma 2.6 we obtain that the set G={k:B∩Bk≠∅} is finite.
Applying Lemma 2.5, if z∈Bk∩B, we get
ρ(xk)≤Cρ(z)(1+|xk−z|ρ(xk))k0≤C2k0ρ(z)≤C2k0ρ(x)(1+|x−z|ρ(x))k0k0+1≤C2k0ρ(x)(1+Rρ(x))≤C2k0R. |
Thus, for every k∈G, we have Bk⊂CB.
Thanks to Lemmas 2.4 and 2.6, it holds that
∫B|f(x)|dx=∫B⋂⋃kBk|f(x)|dx=∫⋃k∈G(B⋂Bk)|f(x)|dx≤∑k∈G∫B∩Bk|f(x)|dx≤∑k∈G∫Bk|f(x)|dx≤C∑k∈G|Bk|αn‖χBk‖p′(⋅)≤C|B|αn‖χB‖p′(⋅). |
The proof of this lemma is completed.
Corollary 1. Assume that p(⋅)∈P(Rn) and 0<α<n, then a measurable function f∈LipLα,p(⋅) if and only if f satisfies (1.4) for every ball B(x,R) with radius R<ρ(x) and
1|B(x,ρ(x))|αn‖χB(x,ρ(x))‖p′(⋅)∫B(x,ρ(x))|f(x)|dx≤C. | (2.3) |
Let kt(x,y) denote the kernel of heat semigroup e−tL associated to L, and Kα(x,y) be the kernel of fractional integral operator Iα, then it holds that
Kα(x,y)=∫∞0kt(x,y)tα2dt. | (2.4) |
Some estimates of kt are presented below.
Lemma 2.8. [12] There exists a constant C such that for N>0,
kt(x,y)≤Ct−n/2e−|x−y|2Ct(1+√tρ(x)+√tρ(y))−N,x,y∈Rn. |
Lemma 2.9. [13] Let 0<δ<min(1,2−nq). If |x−x0|<√t, then for N>0 the kernel kt(x,y) defined in (2.4) satisfies
|kt(x,y)−kt(x0,y)|≤C(|x−x0|√t)δt−n/2e−|x−y|2Ct(1+√tρ(x)+√tρ(y))−N, |
for all x,y and x0 in Rn.
In this section, we are devoted to the proof of Theorems 1.3 and 1.4. To prove Theorem 1.3, thanks to Corollary 1 and Remark 1.2, we only need to prove that the following two conditions hold:
(ⅰ) For every ball B=B(x0,r) with r<ρ(x0), then
∫B|Iαf(x)−c|dx≤C|B|αn‖χB‖p′(⋅)‖f‖p(⋅); |
(ⅱ) For any x0∈Rn, then
∫B(x0,ρ(x0))Iα(|f|)(x)dx≤C|B(x0,ρ(x0))|αn‖χB(x0,ρ(x0))‖p′(⋅)‖f‖p(⋅). |
We now begin to check that these conditions hold. First, we prove (ⅱ).
Assume that B=B(x0,R) and R=ρ(x0). We write f=f1+f2, where f1=fχ2B and f2=fχRn∖2B. Hence, by the inequality (1.3), we have
∫BIα(|f1|)(x)dx=∫BIα(|fχ2B|)(x)dx≤C∫B∫2B|f(y)||x−y|n−αdydx. |
Applying Tonelli theorem, Lemma 2.1 and Remark 1.2, we get the following estimate
∫BIα(|f1|)(x)dx≤C∫2B|f(y)|∫Bdx|x−y|n−αdy≤CRα∫2B|f(y)|dy≤C|B|αn‖χB‖p′(⋅)‖f‖p(⋅). | (3.1) |
To deal with f2, let x∈B and we split Iαf2 as follows:
Iαf2(x)=∫R20e−tLf2(x)tα2−1dt+∫∞R2e−tLf2(x)tα2−1dt:=I1+I2. |
For I1, if x∈B and y∈Rn∖2B, we note that |x0−y|<|x0−x|+|x−y|<C|x−y|. By Lemma 2.8, it holds that
I1=|∫R20∫Rn∖2Bkt(x,y)f(y)dytα2−1dt|≤C∫R20∫Rn∖2Bt−n2e−|x−y|2t|f(y)|dytα2−1dt≤C∫R20t−n+α2−1∫Rn∖2B(t|x−y|2)M/2|f(y)|dydt≤C∫R20tM−n+α2−1dt∫Rn∖2B|f(y)||x0−y|Mdy, |
where the constant C only depends the constant M.
Applying Lemma 2.1 to the last integral, we get
∫Rn∖2B|f(y)||x0−y|Mdy=∞∑i=1∫2i+1B∖2iB|f(y)||x0−y|Mdy≤∞∑i=1(2iR)−M∫2i+1B|f(y)|dy≤C∞∑i=1(2iR)−M‖χ2i+1B‖p′(⋅)‖f‖p(⋅). |
By using Lemma 2.4, we arrive at the inequality
∫Rn∖2B|f(y)||x0−y|Mdy≤C∞∑i=1(R)−M(2i)n−np+−M‖χB‖p′(⋅)‖f‖p(⋅)≤CR−M‖f‖p(⋅)‖χB‖p′(⋅). | (3.2) |
Here, the series above converges when M>n−np+. Hence, for such M,
|∫R20e−tLf2(x)tα2−1dt|≤CR−M‖f‖p(⋅)‖χB‖p′(⋅)∫R20tM−n+α2−1dt≤C|B|αn−1‖f‖p(⋅)‖χB‖p′(⋅). |
For I2, thanks to Lemma 2.8, we may choose M as above and N≥M, then it holds that
|∫∞R2e−tLf2(x)tα−22dt|=|∫∞R2∫Rn∖2Bkt(x,y)f(y)dytα−22dt|≤C∫∞R2∫Rn∖2Btα−n−N−22ρ(x)Ne−|x−y|2t|f(y)|dydt≤Cρ(x)N∫∞R2tα−n−N−22∫Rn∖2B(t|x−y|2)M/2|f(y)|dydt. |
As x∈B, thanks to Lemma 2.5, ρ(x)∼ρ(x0)=R. Hence we have
|∫∞R2e−tLf2(x)tα2−1dt|≤CRN∫∞R2tM+α−n−N2−1dt∫Rn∖2B|f(y)||x0−y|Mdy. |
Since M+α−n−N<0, the integral above for variable t converges, and by applying inequality (3.2) we have
|∫∞R2e−tLf2(x)tα2−1dt|≤C|B|αn−1‖f‖p(⋅)‖χB‖p′(⋅), |
thus we have proved (ⅱ).
We now begin to prove that the condition (ⅰ) holds. Let B=B(x0,r) and r<ρ(x0). We set f=f1+f2 with f1=fχ2B and f2=fχRn∖2B. We write
cr=∫∞r2e−tLf2(x0)tα2−1dt. | (3.3) |
Thanks to (3.1), it holds that
∫B|Iα(f(x))−cr|≤∫BIα(|f1|)(x)dx+∫B|Iα(f2)(x)−cr|dx≤C|B|αn−1‖χB‖p′(⋅)‖f‖p(⋅)+∫B|Iα(f2)(x)−cr|dx. |
Let x∈B and we split Iαf2(x) as follows:
Iαf2(x)=∫r20e−tLf2(x)tα2−1dt+∫∞r2e−tLf2(x)tα2−1dt:=I3+I4. |
For I3, by the same argument it holds that
I3=|∫r20e−tLf2(x)tα2−1dt|≤C|B|αn−1‖f‖p(⋅)‖χB‖p′(⋅). |
For I4, by Lemma 2.9 and (3.3), it follows that
|∫∞r2e−tLf2(x)tα2−1dt−cr|≤∫∞r2∫Rn∖2B|kt(x,y)−kt(x0,y)||f(y)|dytα2−1dt≤Cδ∫∞r2∫Rn∖2B(|x−x0|√t)δt−n/2e−|x−y|2Ct|f(y)|dytα2−1dt≤Cδrδ∫Rn∖2B|f(y)|∫∞r2t−(n−α+δ)/2e−|x−y|2Ctdttdy. |
Let s=|x−y|2t, then we obtain the following estimate
|∫∞r2e−tLf2(x)tα2−1dt−cr|≤Cδrδ∫Rn∖2B|f(y)||x−y|n−α+δdy∫∞0sn−α+δ2e−sCdss. |
Notice that the integral above for variable s is finite, thus we only need to compute the integral above for variable y. Thanks to inequality (3.2), it follows that
|∫∞r2e−tLf2(x)tα2−1dt−cr|≤Cδrδ∫Rn∖2B|f(y)||x−y|n−α+δdy≤C∞∑i=1Rα−n(2i)α−np+−δ‖χB‖p′(⋅)‖f‖p(⋅)≤C|B|α−nn‖f‖p(⋅)‖χB‖p′(⋅), |
so (ⅰ) is proved.
Remark 3.1. By the same argument as the proof of Theorem 1.3, thanks to Lemma 2.2 we immediately obtained that the conclusions of Theorem 1.4 hold.
The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.
Ping Li is partially supported by NSFC (No. 12371136). The authors would like to thank the anonymous referees for carefully reading the manuscript and providing valuable suggestions, which substantially helped in improving the quality of this paper. We also thank Professor Meng Qu for his useful discussions.
The authors declare there are no conflicts of interest.
[1] |
Samsudin AA, Evans PN, Wright AD, et al. (2011) Molecular diversity of the foregut bacteria community in the dromedary camel (Camelus dromedarius). Environ Microbiol 13: 3024-3035. doi: 10.1111/j.1462-2920.2011.02579.x
![]() |
[2] | Kay RNB, Maloiy GMO (1989) Digestive secretions in camels. Options Méditerranéennes–Série Séminaires-n.°2 83-87. |
[3] |
Gharechahi J, Zahiri HS, Noghabi KA, et al. (2015) In-depth diversity analysis of the bacterial community resident in the camel rumen. Syst Appl Microbiol 38: 67-76. doi: 10.1016/j.syapm.2014.09.004
![]() |
[4] |
Lechner-Doll M, Engelhardt WV (1989) Particle size and passage from the forestomach in camels compared to cattle and sheep fed a similar diet. J Anim Physiol Anim Nutr 61: 120-128. doi: 10.1111/j.1439-0396.1989.tb00091.x
![]() |
[5] | Iqbal A, Khan BB (2001) Feeding behaviour of camel. Pak J Agric Sci 38: 58-63. |
[6] |
Samsudin AA, Wright ADG, Al Jassim R (2012) Cellulolytic bacteria in the foregut of the dromedary camel (Camelus dromedarius). Appl Environ Microbiol 78: 8836-8839. doi: 10.1128/AEM.02420-12
![]() |
[7] |
Rabee AE, Forster RJ, Elekwachi CO, et al. (2020) Comparative analysis of the metabolically active microbial communities in the rumen of dromedary camels under different feeding systems using total rRNA sequencing. Peer J 8: e10184. doi: 10.7717/peerj.10184
![]() |
[8] |
Bhatt VD, Dande SS, Patil NV, et al. (2013) Molecular analysis of the bacterial microbiome in the forestomach fluid from the dromedary camel (Camelus dromedarius). Mol Biol Rep 40: 3363-3371. doi: 10.1007/s11033-012-2411-4
![]() |
[9] |
Gharechahi J, Salekdeh GH (2018) A metagenomic analysis of the camel rumen's microbiome identifies the major microbes responsible for lignocellulose degradation and fermentation. Biotechnol Biofuels 11: 216. doi: 10.1186/s13068-018-1214-9
![]() |
[10] |
Ameri R, Laville E, Potocki-VeÂronèse G, et al. (2018) Two new gene clusters involved in the degradation of plant cell wall from the fecal microbiota of Tunisian dromedary. PLoS One 13: e0194621. doi: 10.1371/journal.pone.0194621
![]() |
[11] |
Jami E, White BA, Mizrahi I (2014) Potential role of the bovine rumen microbiome in modulating milk composition and feed ffficiency. PLoS One 9: e85423. doi: 10.1371/journal.pone.0085423
![]() |
[12] |
Moss AR, Jouany JP, Newbold J (2000) Methane production by ruminants: its contribution to global warming. Ann Zootech 49: 231-253. doi: 10.1051/animres:2000119
![]() |
[13] |
Van Nevel CJ, Demeyer DI (1996) Control of rumen methanogenesis. Environ Monit Assess 42: 73-97. doi: 10.1007/BF00394043
![]() |
[14] |
Lee K, Webb RI, Janssen PH, et al. (2009) Phylum Verrucomicrobia representatives share a compartmentalized cell plan with members of bacterial phylum Planctomycetes. BMC Microbiol 9: 5. doi: 10.1186/1471-2180-9-5
![]() |
[15] | Ekinci MS, Özcan N, ÖzkÖse E, et al. (2001) A Study on cellulolytic and hemicellulolytic enzymes of anaerobic rumen bacterium Ruminococcus flavefaciens Strain 17. Turk J Vet Anim Sci 25: 703-709. |
[16] |
Seo JK, Park TS, Kwon IH, et al. (2013) Characterization of cellulolytic and xylanolytic enzymes of Bacillus licheniformis JK7 isolated from the rumen of a native Korean goat. Asian-Aust J Anim Sci 26: 50-58. doi: 10.5713/ajas.2012.12506
![]() |
[17] |
Sadhu S, Ghosh PK, Aditya G, et al. (2014) Optimization and strain improvement by mutation for enhanced cellulase production by Bacillus sp. (MTCC10046) isolated from cow dung. J King Saud UnivSci 26: 323-332. doi: 10.1016/j.jksus.2014.06.001
![]() |
[18] |
Khatab MSA, Abd El Tawab AM, Fouad MT (2017) Isolation and characterization of anaerobic bacteria from frozen rumen liquid and its potential characterization. Int J Dairy Sci 12: 47-51. doi: 10.3923/ijds.2017.47.51
![]() |
[19] |
Selinger LB, Fosberg CW, Cheng KJ (1996) The rumen: A unique source of enzymes for enhancing livestock production. Anaerobe 2: 263-284. doi: 10.1006/anae.1996.0036
![]() |
[20] |
Hess M, Sczyrba A, Egan R, et al. (2011) Metagenomic discovery of biomass degrading genes and genomes from cow rumen. Science 331: 463-467. doi: 10.1126/science.1200387
![]() |
[21] |
Rabee AE, Al Ahl AAS, Sabra EA, et al. (2019a) Assessment of xylanolytic and cellulolytic activities of anaerobic bacterial community in the rumen of camel using different substrates. Menoufia J Animal Poultry Fish Prod 3: 69-82. doi: 10.21608/mjapfp.2019.174814
![]() |
[22] | Molina-Guerrero CE, de la Rosa G, Gonzalez Castañeda J, et al. (2018) Optimization of culture conditions for production of cellulase by Stenotrophomonas maltophilia. Bio Res 13: 8358-8372. |
[23] | Sethi S, Datta A, Gupta BL, et al. (2013) Optimization of Cellulase Production from Bacteria Isolated from Soil. Inter Scholarly Res Not 2013. |
[24] | Rabee AE, Forster RJ, Elekwachi CO, et al. (2019b) Community structure and fibrolytic activities of anaerobic rumen fungi in dromedary camels. J Basic Microbiol 49: 1-10. |
[25] |
Phillips MW, Gordon GLR (1988) Sugar and polysaccharide fermentation by rumen anaerobic fungi from Australia, Britain and New Zealand. BioSystems 21: 377-383. doi: 10.1016/0303-2647(88)90036-6
![]() |
[26] | Wang Z, Elekwachi C, Jiao J, et al. (2017) Changes in Metabolically Active Bacterial Community during Rumen Development, and Their Alteration by Rhubarb Root Powder Revealed by 16S rRNA Amplicon Sequencing. Front Microbiol 8: 159. |
[27] |
Liu K, Xu Q, Wang L, et al. (2016) Comparative studies of the composition of bacterial microbiota associated with the ruminal content, ruminal epithelium and in the faeces of lactating dairy cows. Microb Biotechnol 9: 257-268. doi: 10.1111/1751-7915.12345
![]() |
[28] |
Caporaso JG, Kuczynski J, Stombaugh J, et al. (2010) QIIMEE allows analysis of high-throughput community sequencing data. Nat Methods 7: 335-336. doi: 10.1038/nmeth.f.303
![]() |
[29] | Andrews S Fast QC: a quality control tool for high throughput sequence data (2010) .Available from: http://www.bioinformatics.babraham.ac.uk/projects/fastqc. |
[30] |
Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: A flexible trimmer for Illumina Sequence Data. Bioinformatics 30: 2114-2120. doi: 10.1093/bioinformatics/btu170
![]() |
[31] |
Zhang J, Kobert K, Flouri T, et al. (2014) PEAR: a fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics 30: 614-620. doi: 10.1093/bioinformatics/btt593
![]() |
[32] |
Caldwell DR, Bryant MP (1966) Medium without rumen fluid for nonselective enumeration and isolation of rumen bacteria. Appl Microbiol 14: 794-801. doi: 10.1128/am.14.5.794-801.1966
![]() |
[33] | McSweeney CS, Denman SE, Mackie RI (2005) Rumen bacteria. Methods in Gut Microbial Ecology for Ruminants Dordrecht: Springer. |
[34] | IBM Corp. Released (2011) IBM SPSS Statistics for Windows, Version 20.0 Armonk, NY: IBM Corp. |
[35] |
Petri RM, Schwaiger T, Penner GB, et al. (2013) Characterization of the core rumen microbiome in cattle during transition from forage to concentrate as well as during and after an acidotic challenge. PLoS One 8: e83424. doi: 10.1371/journal.pone.0083424
![]() |
[36] |
Pandya PR, Singh KM, Parnerkar S, et al. (2010) Bacterial diversity in the rumen of Indian Surti buffalo (Bubalus bubalis), assessed by 16S rDNA analysis. J Appl Genet 51: 395-402. doi: 10.1007/BF03208869
![]() |
[37] |
Pitta DW, Kumar S, Veiccharelli B, et al. (2014) Bacterial diversity associated with feeding dry forage at different dietary concentrations in the rumen contents of Mehshana buffalo (Bubalus bubalis) using 16S pyrotags. Anaerobe 25: 31-41. doi: 10.1016/j.anaerobe.2013.11.008
![]() |
[38] | Naas AE, Mackenzie AK, Mravec J, et al. (2014) Do rumen Bacteroidetes utilize an alternative mechanism for cellulose degradation? mBio 5: e01401-e01414. |
[39] |
Fouts DE, Szpakowski S, Purushe J, et al. (2012) Next generation sequencing to define prokaryotic and fungal diversity in the bovine rumen. PLoS One 7: e48289. doi: 10.1371/journal.pone.0048289
![]() |
[40] |
Russell JB, Rychlik JL (2001) Factors that alter rumen microbial ecology. Science 292: 1119-1122. doi: 10.1126/science.1058830
![]() |
[41] |
Nathani NM, Patel AK, Mootapally CS, et al. (2015) Effect of roughage on rumen microbiota composition in the efficient feed converter and sturdy Indian Jaffrabadi buffalo (Bubalus bubalis). BMC Genomics 16: 1116. doi: 10.1186/s12864-015-2340-4
![]() |
[42] |
Koike S, Yoshitani S, Kobayashi Y, et al. (2003) Phylogenetic analysis of fiber-associated rumen bacterial community and PCR detection of uncultured bacteria. FEMS Microbiol Lett 229: 23-30. doi: 10.1016/S0378-1097(03)00760-2
![]() |
[43] |
Liu K, Xu Q, Wang L, et al. (2017) The impact of diet on the composition and relative abundance of rumen microbes in goat. Asian-Australas J Anim Sci 30: 531-537. doi: 10.5713/ajas.16.0353
![]() |
[44] |
Gruninger RJ, McAllister TA, Forster RJ (2016) Bacterial and archaeal diversity in the gastrointestinal tract of the orth American beaver (Castor canadensis). PLoS One 11: e0156457. doi: 10.1371/journal.pone.0156457
![]() |
[45] |
Ransom-Jones E, Jones DL, McCarthy AJ, et al. (2012) The Fibrobacteres: an important phylum of cellulose-degrading bacteria. Microb Ecol 63: 267-281. doi: 10.1007/s00248-011-9998-1
![]() |
[46] |
Ishaq SL, Wright AG (2012) Insight into the bacterial gut microbiome of the North American moose (Alces alces). BMC Microbiol 12: 212. doi: 10.1186/1471-2180-12-212
![]() |
[47] |
Leahy S, Kelly W, Ronimus R, et al. (2013) Genome sequencing of rumen bacteria and archaea and its application to methane mitigation strategies. Animal 7: 235-243. doi: 10.1017/S1751731113000700
![]() |
[48] |
Herlemann DPR, Geissinger O, Ikeda-Ohtsubo W, et al. (2009) Genomic analysis of “Elusimicrobium minutum,” the first cultivated representative of the phylum “Elusimicrobia” (formerly termite group 1). Appl Environ Microbiol 70: 2841-2849. doi: 10.1128/AEM.02698-08
![]() |
[49] | Ishaq S, Sundset M, Crouse J, et al. (2015) High-throughput DNA sequencing of the moose rumen from different geographical locations reveals a core ruminal methanogenic archaeal diversity and a differential ciliate protozoal diversity. Microb Genom 1: e000034. |
[50] |
Zoetendal E, Plugge CM, Akkermans ADL, et al. (2003) Victivallisvadensis gen. nov., sp. nov., a sugar-fermenting anaerobe from human faeces. Int J Syst Evol Microbiol 53: 211-215. doi: 10.1099/ijs.0.02362-0
![]() |
[51] |
Jewell KA, McComirck C, Odt CL, et al. (2015) Ruminal bacterial community composition in dairy cows is dynamic over the course of two lactations and correlates with feed efficiency. Appl Environ Microbiol 18: 4697-4710. doi: 10.1128/AEM.00720-15
![]() |
[52] | Noel SJ, Højberg O, Urich T, et al. (2016) Draft genome sequence of “Candidatus Methanomethylophilus” sp. 1R26, enriched from bovine rumen, a methanogenic archaeon belonging to the Methanomassiliicoccales order. Genome Announc 4: e01734-e01715. |
[53] | Zorec M, Vodovnik M, MarinŠek-Logar R, et al. (2014) Potential of selected rumen bacteria for cellulose and hemicellulose degradation. Food Technol Biotechnol 52: 210-221. |
[54] |
Henderson G, Cox F, Ganesh S, et al. (2015) Rumen microbial community composition varies with diet and host, but a core microbiome is found across a wide geographical range. Sci Rep 5: 14567. doi: 10.1038/srep14567
![]() |
[55] |
Carberry CA, Kenny DA, Han S, et al. (2012) Effect of phenotypic residual feed intake and dietary forage content on the rumen microbial community of beef cattle. Appl Environ Microbiol 78: 4949-4958. doi: 10.1128/AEM.07759-11
![]() |
[56] |
Shrivastava B, Jain KK, Kalra A, et al. (2014) Bioprocessing of wheat straw into nutritionally rich and digested cattle feed. Sci Rep 4: 6360. doi: 10.1038/srep06360
![]() |
[57] |
Asem D, Leo VV, Passari AK, et al. (2017) Evaluation of gastrointestinal bacterial population for the production of holocellulose enzymes for biomass deconstruction. PLoS One 12: e0186355. doi: 10.1371/journal.pone.0186355
![]() |
[58] |
Salmon DNX, Spier MR, Soccol CR, et al. (2014) Analysis of inducers of xylanase and cellulase activities production by Ganoderma applanatum LPB MR-56. Fungal Biol 118: 655-662. doi: 10.1016/j.funbio.2014.04.003
![]() |
[59] |
Williams AG, Withers SE (1982) The production of plant cell wall polysaccharide-degrading enzymes by hemicellulolytic rumen bacterial isolates grown on a range of carbohydrate substrates. J Appl Bacteriol 52: 377-387. doi: 10.1111/j.1365-2672.1982.tb05068.x
![]() |
[60] |
Yang W, Meng F, Peng J, et al. (2014) Isolation and identification of a cellulolytic bacterium from the Tibetan pig's intestine and investigation of its cellulase production. Electron J Biotechnol 17: 262-267. doi: 10.1016/j.ejbt.2014.08.002
![]() |
[61] | Hook SE, Wright ADG, McBride BW (2010) Methanogens: methane producers of the rumen and mitigation strategies. Archaea 2010: 945785. |
[62] |
St-Pierre B, Wright AG (2012) Molecular analysis of methanogenic archaea in the forestomach of the alpaca (Vicugna pacos). BMC Microbiol 12: 1. doi: 10.1186/1471-2180-12-1
![]() |
[63] | Salgado-Flores A, Bockwoldt M, Hagen L, et al. (2016) First insight into the faecal microbiota of the high Arctic muskoxen (Ovibos moschatus). Microb Genom 2. |
[64] |
Franzolin R, Wright AG (2016) Microorganisms in the rumen and reticulum of buffalo (Bubalus bubalis) fed two different feeding systems. BMC Research Notes 9: 243. doi: 10.1186/s13104-016-2046-y
![]() |
![]() |
![]() |
![]() |
![]() |