The transition from a traditional linear economy to a circular model aims to create a more sustainable future by reducing the adverse effects of agro-waste on the environment. The present study evaluated the metabolic diversity of bacterial isolates from municipal dumpsites for keratinase production and poultry feather valorization. The bacterium with the highest keratinolytic activity was identified through 16S ribosomal ribonucleic acid (rRNA) gene sequencing. The exo-keratinase production by the bacterium was optimized, and the feather hydrolysate obtained from the fermentation process was analyzed for amino acids. Among the twelve bacteria isolated from the dumpsite's sample, three showed significant feather degradation and keratinase production of 89% (744.5 ± 9.19 U/mL), 58% (269 ± 15.55 U/mL), and 46% (195 ± 7.07 U/mL) for SSB-03, SSB-02, and HSB-02, respectively. Analysis of the 16S rRNA gene sequence revealed that SSB-03 has high sequence homology with Exiguobacterium acetylicum, and thus, it was identified as Exiguobacterium acetylicum FHBD (accession number MW165834). Strain FHBD fermentation medium exhibited the maximum keratinase activity (2934.54 ± 38.56 U/mL) and sulfhydryl group content (3.09 ± 0.02 mM) at 72 h under optimal process conditions of pH 5.0, temperature (35 °C), inoculum size (2% v/v), and feather (15 g/L). Amino acid analysis of the feather hydrolysate showed significant levels of glutamic acid, aspartic acid, glycine, arginine, serine, and proline, with respective concentrations of 1.58, 1.34, 1.29, 1.20, 1.12, and 0.93 (g/100 g of sample). The study's findings emphasize the potential of E. acetylicum FHBD in poultry feather valorization and keratinase production.
Citation: Tutuka Dlume, Nonso E. Nnolim, Uchechukwu U. Nwodo. Exiguobacterium acetylicum transformed poultry feathers into amino acids through an extracellular secretion of keratinolytic enzymes[J]. AIMS Bioengineering, 2024, 11(4): 489-505. doi: 10.3934/bioeng.2024022
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The transition from a traditional linear economy to a circular model aims to create a more sustainable future by reducing the adverse effects of agro-waste on the environment. The present study evaluated the metabolic diversity of bacterial isolates from municipal dumpsites for keratinase production and poultry feather valorization. The bacterium with the highest keratinolytic activity was identified through 16S ribosomal ribonucleic acid (rRNA) gene sequencing. The exo-keratinase production by the bacterium was optimized, and the feather hydrolysate obtained from the fermentation process was analyzed for amino acids. Among the twelve bacteria isolated from the dumpsite's sample, three showed significant feather degradation and keratinase production of 89% (744.5 ± 9.19 U/mL), 58% (269 ± 15.55 U/mL), and 46% (195 ± 7.07 U/mL) for SSB-03, SSB-02, and HSB-02, respectively. Analysis of the 16S rRNA gene sequence revealed that SSB-03 has high sequence homology with Exiguobacterium acetylicum, and thus, it was identified as Exiguobacterium acetylicum FHBD (accession number MW165834). Strain FHBD fermentation medium exhibited the maximum keratinase activity (2934.54 ± 38.56 U/mL) and sulfhydryl group content (3.09 ± 0.02 mM) at 72 h under optimal process conditions of pH 5.0, temperature (35 °C), inoculum size (2% v/v), and feather (15 g/L). Amino acid analysis of the feather hydrolysate showed significant levels of glutamic acid, aspartic acid, glycine, arginine, serine, and proline, with respective concentrations of 1.58, 1.34, 1.29, 1.20, 1.12, and 0.93 (g/100 g of sample). The study's findings emphasize the potential of E. acetylicum FHBD in poultry feather valorization and keratinase production.
Minimal salt media;
Ground chicken feather;
Polymerase chain reaction;
National Centre for Biotechnology Information;
Basic local alignment search tool
Some special polynomials and numbers are diversely used in physics and engineering as well as in mathematics. For example, Bell polynomials play an important role in the studies of water waves which help energy development, mechanical engineering, marine/offshore engineering, hydraulic engineering, etc (see [9,10,11,12,22]). There are various ways of studying special numbers and polynomials, to mention a few, generating functions, combinatorial methods, p-adic analysis, umbral calculus, differential equations, probability theory, special functions and analytic number theory (see [1,2]).
The aim of this paper is to introduce several special polynomials and numbers, and to study their explicit expressions, recurrence relations and identities involving those polynomials and numbers by using generating functions.
Indeed, we introduce Bell polynomials and numbers of the second kind (see (2.3), (2.5)) and poly-Bell polynomials and numbers of the second kind (see (4.1)). The generating function of Bell numbers of the second kind is the compositional inverse of the generating function of Bell numbers minus the constant term. Then Bell polynomials of the second kind are natural extensions of those numbers (see [23]). The poly-Bell polynomials of the second kind, which are defined with the help of polylogarithm, become the Bell polynomials of the second kind up to sign when the index of the polylogarithm is k=1.
We also consider degenerate versions of those numbers and polynomials, namely degenerate Bell numbers and polynomials of the second (see (3.3), (3.5)) and degenerate poly-Bell numbers and polynomials (see (5.1)), and derive similar results. It is worthwhile to note that degenerate versions of many special numbers and polynomials have been explored in recent years with aforementioned tools and many interesting arithmetical and combinatorial results have been obtained (see [14,15,18,19,26]). In fact, studying degenerate versions can be done not only for polynomials and numbers but also for transcendental functions like gamma functions. For the rest of this section, we recall the necessary facts that are needed throughout this paper.
The Stirling numbers of the first kind, S1(n,k), are given by
1k!(log(1+t))k=∞∑n=kS1(n,k)tnn!,(k≥0),(see [7,25]), | (1.1) |
As the inversion formula of (1.1), the Stirling numbers of the second kind, S2(n,k), are given by
1k!(et−1)k=∞∑n=kS2(n,k)tnn!,(k≥0),(see [3,13−20]). | (1.2) |
It is well known that the Bell polynomials are defined as
Beln(x)=n∑k=0S2(n,k)xk,(n≥0),(see [24,25]). | (1.3) |
From (1.3), we note that
ex(et−1)=∞∑n=0Beln(x)tnn!,(see [4,7,8,17,27]). | (1.4) |
When x=1, Beln=Beln(1), (n≥0) are called the Bell numbers.
For any λ∈R, the degenerate exponential function is given by
exλ(t)=∞∑n=0(x)n,λn!tn,(see [5,6,7,26,27]), | (1.5) |
where (x)0,λ=1, (x)n,λ=x(x−λ)⋯(x−(n−1)λ), (n≥1).
When x=1, we write eλ(t)=e1λ(t).
The degenerate Stirling numbers of the first kind are defined by
1k!(logλ(1+t))k=∞∑n=kS1,λ(n,k)tnn!, (k≥0), (see [15]), | (1.6) |
where
logλ(1+t)=∞∑n=1λn−1(1)n,1/λtnn!,(see [15]). | (1.7) |
In view of (1.2), the degenerate Stirling numbers of the second kind are defined by
1k!(eλ(t)−1)k=∞∑n=kS2(n,k)tnn!,(see [15]). | (1.8) |
In [17], the degenerate Bell polynomials are defined by
exλ(eλ(t)−1)=∞∑n=0Beln,λ(x)tnn!. | (1.9) |
When x=1, Beln,λ=Beln,λ(1), (n≥0), are called the Bell numbers.
From (1.8) and (1.9), we note that
Beln,λ(x)=n∑k=0S2,λ(n,k)(x)k,λ, (n≥0), (see [17]). | (1.10) |
The polylogarithm of index k is given by
Lik(x)=∞∑n=1xnnk,(k∈Z, |x|<1),(see [3,13,14,16,21]). | (1.11) |
Note that Li1(x)=−log(1−x).
Recently, the degenerate polylogarithm is defined as
Lik,λ(x)=∞∑n=1(−λ)n−1(1)n,1/λ(n−1)!nkxn,(|x|<1, k∈Z),(see [15]). | (1.12) |
Note that Li1,λ(x)=−logλ(1−x).
Here we mention that, to our best knowledge, the results of this paper are new.
From (1.4), we note that
ex(et−1)=∞∑n=0Beln(x)tnn! |
Let x=1. Then we have
eet−1−1=∞∑n=1Belntnn!. | (2.1) |
Let f(t)=eet−1−1. Then the compositional inverse of f(t) is given by
f−1(t)=log(1+log(1+t)). | (2.2) |
We consider the new type Bell numbers, called Bell numbers of the second kind, defined by
log(1+log(1+t))=∞∑n=1belntnn!. | (2.3) |
Now, we observe that
log(1+log(1+t))=∞∑k=1(−1)k−1k(log(1+t))k=∞∑k=1(−1)k−1(k−1)!1k!(log(1+t))k=∞∑k=1(−1)k−1(k−1)!∞∑n=kS1(n,k)tnn!=∞∑n=1(n∑k=1(−1)k−1(k−1)!S1(n,k))tnn!. | (2.4) |
Therefore, by (2.3) and (2.4), we obtain the following theorem.
Theorem 1. For n≥1, we have
(−1)n−1beln=n∑k=1(k−1)![nk], |
where [nk] are the unsigned Stirling numbers of the first kind.
Also, we consider the new type Bell polynomials, called Bell polynomials of the second kind, defined by
beln(x)=n∑k=1(−1)k−1(k−1)!S1(n,k)xk,(n≥1). | (2.5) |
From (2.5), we can derive the following equation.
∞∑n=1beln(x)tnn!=∞∑n=1(n∑k=1(−1)k−1(k−1)!S1(n,k)xk)tnn!=∞∑k=1(−1)k−1(k−1)!xk∞∑n=kS1(n,k)tnn!=∞∑k=1(−1)k−1k!kxk1k!(log(1+t))k=∞∑k=1(−1)k−1kxk(log(1+t))k=log(1+xlog(1+t)). | (2.6) |
Thus the generating function of Bell polynomials of the second kind is given by
log(1+xlog(1+t))=∞∑n=1beln(x)tnn!. | (2.7) |
Note here that beln=beln(1). From (2.7), we note that
x(1+xlog(1+t))(1+t)=ddtlog(1+xlog(1+t))=∞∑n=0beln+1(x)tnn!. | (2.8) |
Replacing t by et−1 in (2.8), we get
x1+xte−t = ∞∑k=0belk+1(x)1k!(et−1)k= ∞∑k=0belk+1(x)∞∑n=kS2(n,k)tnn!= ∞∑n=0(n∑k=0belk+1(x)S2(n,k))tnn!. | (2.9) |
Taking x=−1 in (2.9), we have
∞∑n=0(n∑k=0belk+1(−1)S2(n,k))tnn!=−11−te−t=−∞∑n=0dntnn!, | (2.10) |
where dn is the derangement number (see [19]).
Therefore, by comparing the coefficients on both sides of (2.10), we obtain the following theorem.
Theorem 2. For n≥0, we have
n∑k=0belk+1(−1)S2(n,k)=−dn. |
Replacing t by eet−1−1 in (2.3), we get
t=∞∑k=1belk1k!(eet−1−1)k=∞∑k=1belk∞∑j=kS2(j,k)1j!(et−1)j=∞∑j=1j∑k=1belkS2(j,k)∞∑n=jS2(n,k)tnn!=∞∑n=1(n∑j=1j∑k=1belkS2(j,k)S2(n,j))tnn!. | (2.11) |
Thus we obtain following theorem.
Theorem 3. For n≥2, we have
n∑j=1j∑k=1belkS2(j,k)S2(n,j)=0,andbel1=1. |
Replacing t by et−1 in (2.7), we get
log(1+xt) = ∞∑k=1belk(x)1k!(et−1)k= ∞∑k=1belk(x)∞∑n=kS2(n,k)tnn!= ∞∑n=1(n∑k=1belk(x)S2(n,k))tnn!. | (2.12) |
On the other hand,
log(1+xt)=∞∑n=1(−1)n−1nxntn. | (2.13) |
Therefore, by (2.12) and (2.13), we obtain the following theorem.
Theorem 4. For n≥1, we have
xn=(−1)n−1(n−1)!n∑k=1belk(x)S2(n,k). |
In particular,
1=(−1)n−1(n−1)!n∑k=1belkS2(n,k). |
From (1.3), we note that
eλ(eλ(t)−1)−1=∞∑n=1Beln,λtnn!. | (3.1) |
Let fλ(t)=eλ(eλ(t)−1)−1. Then the compositional inverse of fλ(t) is given by
f−1λ(t)=logλ(1+logλ(1+t)). | (3.2) |
We consider the new type degenerate Bell numbers, called degenerate Bell numbers of the second kind, defined by
logλ(1+logλ(1+t))=∞∑n=1beln,λtnn!. | (3.3) |
Now, we observe that
logλ(1+logλ(1+t)) = ∞∑k=1λk−1(1)k,1/λ1k!(logλ(1+t))k= ∞∑k=1λk−1(1)k,1/λ∞∑n=kS1,λ(n,k)tnn!.= ∞∑n=1(n∑k=1λk−1(1)k,1/λS1,λ(n,k))tnn!. | (3.4) |
Therefore, by (3.3) and (3.4), we obtain the following theorem.
Theorem 5. For n≥1, we have
beln,λ=n∑k=1λk−1(1)k,1/λS1,λ(n,k). |
Also, we define the degenerate Bell polynomials of second kind by
beln,λ(x)=n∑k=1λk−1(1)k,1/λS1,λ(n,k)xk. | (3.5) |
Note that beln,λ=beln,λ(1).
From (3.5), we note that
∞∑n=1beln,λ(x)tnn! = ∞∑n=1(n∑k=1λk−1(1)k,1/λS1,λ(n,k)xk)tnn!= ∞∑k=1λk−1(1)k,1/λxk∞∑n=kS1,λ(n,k)tnn!= ∞∑k=1λk−1(1)k,1/λxk1k!(logλ(1+t))k= logλ(1+xlogλ(1+t)). | (3.6) |
Thus the generating function of beln,λ(x) is given by
logλ(1+xlogλ(1+t))=∞∑n=1beln,λ(x)tnn!. | (3.7) |
Replacing t by eλ(t)−1 in (3.7), we get
logλ(1+xt) = ∞∑k=1belk,λ(x)1k!(eλ(t)−1)k= ∞∑k=1belk,λ(x)∞∑n=kS2,λ(n,k)tnn!= ∞∑n=1(n∑k=1belk,λ(x)S2,λ(n,k))tnn!. | (3.8) |
On the other hand,
logλ(1+xt)=∞∑n=1λn−1(1)n,1/λxntnn!. | (3.9) |
Therefore, by (3.8) and (3.9), we obtain the following theorem.
Theorem 6. For n≥1, we have
xn=λ1−n(1)n,1/λn∑k=1belk,λ(x)S2,λ(n,k). |
In particular,
λn−1(1)n,1/λ=n∑k=1belk,λS2,λ(n,k). |
Replacing t by eλ(eλ(t)−1)−1 in (3.3), we have
t =∞∑k=1belk,λ1k!(eλ(eλ(t)−1)−1)k=∞∑k=1belk,λ∞∑j=kS2,λ(j,k)1j!(eλ(t)−1)j= ∞∑j=1(j∑k=1belk,λS2,λ(j,k))∞∑n=jS2,λ(n,j)tnn!= ∞∑n=1(n∑j=1j∑k=1belk,λS2,λ(j,k)S2,λ(n,j))tnn!. | (3.10) |
Therefore, by comparing the coefficients on both sides of (3.10), we obtain the following theorem.
Theorem 7. For n≥2, we have
n∑j=1j∑k=1belk,λS2,λ(j,k)S2,λ(n,j)=0,andbel1,λ=1. |
Now, we consider the poly-Bell polynomials of the second kind which are defined as
Lik(−xlog(1−t))=∞∑n=1bel(k)n(x)tnn!. | (4.1) |
When x=1, bel(k)n=bel(k)n(1) are called the poly-Bell numbers of the second kind.
From (1.11), we note that
Lik(−xlog(1−t)) = ∞∑l=1(−1)llkxll!1l!(log(1−t))l= ∞∑l=1(−1)llk−1(l−1)!xl∞∑n=l(−1)nS1(n,l)tnn!= ∞∑n=1(n∑l=1(−1)n−llk−1(l−1)!xlS1(n,l))tnn!. | (4.2) |
Therefore, by (4.1) and (4.2), we obtain the following theorem.
Theorem 8. For n≥1, we have
bel(k)n(x)=n∑l=1xllk−1(l−1)![nl]. |
In particular,
bel(k)n=n∑l=11lk−1(l−1)![nl]. |
Note that
bel(1)n(x)=n∑l=1xl(l−1)![nl]=(−1)n−1beln(x). |
Indeed,
Li1(−xlog(1−t)) = −log(1+xlog(1−t))= ∞∑n=1beln(x)(−1)n−1tnn!. |
Replacing t by 1−e−t in (4.1), we get
Lik(xt) = ∞∑l=1bel(k)l(x)1l!(1−e−t)l= ∞∑l=1bel(k)l(x)(−1)l∞∑n=lS2(n,l)(−1)ntnn!.= ∞∑n=1(n∑l=1(−1)n−lbel(k)l(x)S2(n,l))tnn!. | (4.3) |
From (1.11) and (4.3), we note that
xnnk=1n!n∑l=1(−1)n−lbel(k)l(x)S2(n,l). | (4.4) |
Therefore, by (4.4), we obtain the following theorem.
Theorem 9. For n≥1, we have
xn=nk−1(n−1)!n∑l=1(−1)n−lbel(k)l(x)S2(n,l). |
We define the degenerate poly-Bell polynomials of the second kind by
Lik,λ(−xlogλ(1−t))=∞∑n=1bel(k)n,λ(x)tnn!. | (5.1) |
When x=1, bel(k)n,λ=bel(k)n,λ(1) are called the degenerate poly-Bell numbers of the second.
From (2.1), we note that
Lik,λ(−xlogλ(1−t) = ∞∑l=1(−λ)l−1(1)l,1/λ(l−1)!lk(−xlogλ(1−t))l= −∞∑l=1(1)l,1/λlk−1λl−1xl1l!(logλ(1−t))l.=−∞∑l=1(1)l,1/λlk−1λl−1xl∞∑n=lS1,λ(n,l)(−1)ntnn!= ∞∑n=1((−1)n−1n∑l=11lk−1(1)l,1/λλl−1xlS1,λ(n,l))tnn!. | (5.2) |
Therefore, by (5.1) and (5.2), we obtain the following theorem.
Theorem 10. For n≥1, we have
(−1)n−1bel(k)n,λ(x)=n∑l=11lk−1(1)l,1/λλl−1xlS1,λ(n,l). |
For k=1, we have
(−1)n−1bel(1)n,λ(x)=n∑l=1(1)l,1/λλl−1xlS1,λ(n,l)=beln,λ(x),(n≥0). |
Indeed,
Li1,λ(−xlogλ(1−t))=−logλ(1+xlogλ(1−t))=∞∑n=1(−1)n−1beln,λ(x)tnn!. |
Replacing t by 1−eλ(−t) in (5.1), we get
Lik,λ(xt) = ∞∑l=1bel(k)l,λ(x)1l!(1−eλ(−t))l= ∞∑l=1bel(k)l,λ(x)(−1)l1l!(eλ(−t)−1)l= ∞∑l=1bel(k)l,λ(x)(−1)l∞∑n=lS2,λ(n,l)(−1)ntnn!= ∞∑n=1(n∑l=1(−1)n−lbel(k)l,λ(x)S2,λ(n,l))tnn!. | (5.3) |
On the other hand,
Lik,λ(xt)=∞∑n=1(−λ)n−1(1)n,1/λ(n−1)!nkxntn=∞∑n=1(−λ)n−1(1)n,1/λnk−1xntnn!. | (5.4) |
From (5.3) and (5.4), we get the following result.
Theorem 11. For n≥1, we have
(−λ)n−1(1)n,1/λnk−1xn=n∑l=1(−1)n−lbel(k)l,λ(x)S2,λ(n,l). |
Many special polynomials and numbers are widely used in physics and engineering as well as in mathematics. In recent years, degenerate versions of some special polynomials and numbers have been studied by means of various different tools. Here we introduced Bell polynomials of the second kind, poly-Bell polynomials of the second kind and their degenerate versions, namely degenerate Bell polynomials of the second kind and degenerate poly-Bell polynomials of the second kind. By using generating functions, we explored their explicit expressions, recurrence relations and some identities involving those polynomials and numbers.
It is one of our future projects to continue this line of research, namely to explore many special numbers and polynomials and their degenerate versions with the help of various different tools.
This work was supported by the Basic Science Research Program, the National Research Foundation of Korea, (NRF-2021R1F1A1050151).
The authors declare no conflict of interest.
[1] |
Muscat A, de Olde EM, Ripoll-Bosch R, et al. (2021) Principles, drivers and opportunities of a circular bioeconomy. Nat Food 2: 561-566. https://doi.org/10.1038/s43016-021-00340-7 ![]() |
[2] |
Velenturf AP, Purnell P (2021) Principles for a sustainable circular economy. Sustain Prod Consum 27: 1437-1457. https://doi.org/10.1016/j.spc.2021.02.018 ![]() |
[3] |
Choi J, Kong B, Bowker BC, et al. (2023) Nutritional strategies to improve meat quality and composition in the challenging conditions of broiler production: a review. Animals 13: 1386. https://doi.org/10.3390/ani13081386 ![]() |
[4] |
Zhang F, Jiang L, Wang S (2018) Repairable cascaded slide-lock system endows bird feathers with tear-resistance and superdurability. Proc Natl Acad Sci 115: 10046-10051. https://doi.org/10.1073/pnas.1808293115 ![]() |
[5] |
Li ZW, Liang S, Ke Y, et al. (2020) The feather degradation mechanisms of a new Streptomyces sp. isolate SCUT-3. Commun Biol 3: 191. https://doi.org/10.1038/s42003-020-0918-0 ![]() |
[6] |
Chilakamarry CR, Mahmood S, Saffe SNBM, et al. (2021) Extraction and application of keratin from natural resources: a review. 3 Biotech 11: 1-12. https://doi.org/10.1007/s13205-021-02734-7 ![]() |
[7] |
Srivastava B, Khatri M, Singh G, et al. (2020) Microbial keratinases: an overview of biochemical characterization and its eco-friendly approach for industrial applications. J Clean Prod 252: 119847. https://doi.org/10.1016/j.jclepro.2019.119847 ![]() |
[8] |
Dawan J, Ahn J (2022) Bacterial stress responses as potential targets in overcoming antibiotic resistance. Microorganisms 10: 1385. https://doi.org/10.3390/microorganisms10071385 ![]() |
[9] |
Alwakeel SS, Ameen F, Al Gwaiz H, et al. (2021) Keratinases produced by Aspergillus stelliformis, Aspergillus sydowii, and Fusarium brachygibbosum isolated from human hair: yield and activity. J Fungi 7: 471. https://doi.org/10.3390/jof7060471 ![]() |
[10] | Derhab N, Mabrouk ME, El-Metwally MM, et al. (2023) Thermostable keratinase from Bacillus cereus L10: optimization and some potential biotechnological applications. Biomass Convers Bioref 2023: 1-17. https://doi.org/10.1007/s13399-023-04887-2 |
[11] |
Williams CM, Richter CS, MacKenzie Jr JM, et al. (1990) Isolation, identification, and characterization of a feather-degrading bacterium. Appl Environ Microbiol 56: 1509-1515. https://doi.org/10.1128/aem.56.6.1509-1515.1990 ![]() |
[12] |
Yahaya RSR, Phang LY, Normi YM, et al. (2022) Feather-degrading Bacillus cereus HD1: genomic analysis and its optimization for keratinase production and feather degradation. Curr Microbiol 79: 166. https://doi.org/10.1007/s00284-022-02861-1 ![]() |
[13] |
Peng Z, Mao X, Zhang J, et al. (2019) Effective biodegradation of chicken feather waste by co-cultivation of keratinase producing strains. Microb Cell Fact 18: 1-11. https://doi.org/10.1186/s12934-019-1134-9 ![]() |
[14] |
Park G, Lee KM, Lee YS, et al. (2023) Biodegradation and valorization of feather waste using the keratinase-producing bacteria and their application in environmentally hazardous industrial processes. J Environ Manag 346: 118986. https://doi.org/10.1016/j.jenvman.2023.118986 ![]() |
[15] |
Gurav RG, Tang J, Jadhav JP (2016) Sulfitolytic and keratinolytic potential of Chryseobacterium sp. RBT revealed hydrolysis of melanin containing feathers. 3 Biotech 6: 145. https://doi.org/10.1007/s13205-016-0464-0 ![]() |
[16] |
Łaba W, Żarowska B, Chorążyk D, et al. (2018) New keratinolytic bacteria in valorization of chicken feather waste. AMB Express 8: 9. https://doi.org/10.1186/s13568-018-0538-y ![]() |
[17] |
Abdelmoteleb A, Gonzalez-Mendoza D, Tzintzun-Camacho O, et al. (2023) Keratinases from Streptomyces netropsis and Bacillus subtilis and their potential use in the chicken feather degrading. Fermentation 9: 96. https://doi.org/10.3390/fermentation9020096 ![]() |
[18] |
Kshetri P, Singh PL, Chanu SB, et al. (2022) Biological activity of peptides isolated from feather keratin waste through microbial and enzymatic hydrolysis. Electron J Biotechnol 60: 11-18. https://doi.org/10.1016/j.ejbt.2022.08.001 ![]() |
[19] | Lai Y, Wu X, Zheng X, et al. (2023) Insights into the keratin efficient degradation mechanism mediated by Bacillus sp. CN2 based on integrating functional degradomics. Biotechnol Biof Biop 16: 59. https://doi.org/10.1186/s13068-023-02308-0 |
[20] |
El-Gindy AA, Ibrahim ZM, Aziz HM, et al. (2023) Chicken feather waste degradation by Malbranchea cinnamomea and its application on plant growth and metabolites of Vicia faba plant. Biocatal Agric Biotechnol 53: 102883. https://doi.org/10.1016/j.bcab.2023.102883 ![]() |
[21] |
Zengler K, Zaramela LS (2018) The social network of microorganisms—how auxotrophies shape complex communities. Nat Rev Microbiol 16: 383-390. https://doi.org/10.1038/s41579-018-0004-5 ![]() |
[22] |
Letourneau F, Soussotte V, Bressollier P, et al. (1998) Keratinolytic activity of Streptomyces sp. S. K1–02: a new isolated strain. Lett Appl Microbiol 26: 77-80. https://doi.org/10.1046/j.1472-765X.1998.00281.x ![]() |
[23] |
Riffel A, Brandelli A (2006) Keratinolytic bacteria isolated from feather waste. Braz J Microbiol 37: 395-399. https://doi.org/10.1590/S1517-83822006000300036 ![]() |
[24] |
Bokveld A, Nnolim NE, Digban TO, et al. (2023) Chryseobacterium aquifrigidense keratinase liberated essential and nonessential amino acids from chicken feather degradation. Environ Technol 44: 293-303. https://doi.org/10.1080/09593330.2021.1969597 ![]() |
[25] |
Nnolim NE, Okoh AI, Nwodo UU (2020) Proteolytic bacteria isolated from agro-waste dumpsites produced keratinolytic enzymes. Biotechnol Rep 27: e00483. https://doi.org/10.1016/j.btre.2020.e00483 ![]() |
[26] |
Bradford MM (1976) A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem 72: 248-254. https://doi.org/10.1016/0003-2697(76)90527-3 ![]() |
[27] |
Ellman GL (1959) Tissue sulfhydryl groups. Arch Biochem Biophys 82: 70-77. https://doi.org/10.1016/0003-9861(59)90090-6 ![]() |
[28] |
Turner S, Pryer KM, Miao VP, et al. (1999) Investigating deep phylogenetic relationships among cyanobacteria and plastids by small subunit rRNA sequence analysis1. J Eukaryot Microbiol 46: 327-338. https://doi.org/10.1111/j.1550-7408.1999.tb04612.x ![]() |
[29] |
Altschul SF, Madden TL, Schäffer AA, et al. (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25: 3389-3402. https://doi.org/10.1093/nar/25.17.3389 ![]() |
[30] |
Einarsson S, Josefsson B, Lagerkvist S (1983) Determination of amino acids with 9-fluorenylmethyl chloroformate and reversed-phase high-performance liquid chromatography. J Chromatogr A 282: 609-618. https://doi.org/10.1016/S0021-9673(00)91638-8 ![]() |
[31] |
Bank RA, Jansen EJ, Beekman B, et al. (1996) Amino acid analysis by reverse-phase high-performance liquid chromatography: improved derivatization and detection conditions with 9-fluorenylmethyl chloroformate. Anal Biochem 240: 167-176. https://doi.org/10.1006/abio.1996.0346 ![]() |
[32] |
Ke H, Li J, Zhang X, et al. (2022) Bacterial community structure and predicted metabolic function of landfilled municipal solid waste in China. Sustainability 14: 3144. https://doi.org/10.3390/su14063144 ![]() |
[33] | Gumilar J, Triatmojo S, Yusiati LM, et al. (2015) Isolation, identification and dehairing activity of Indonesian native keratinolytic bacteria Exiguobacterium sp. DG1. Pak J Biotechnol 12: 41-48. https://pjbt.org/index.php/pjbt/article/view/128 |
[34] |
Emon TH, Hakim A, Chakraborthy D, et al. (2020) Kinetics, detergent compatibility and feather-degrading capability of alkaline protease from Bacillus subtilis AKAL7 and Exiguobacterium indicum AKAL11 produced with fermentation of organic municipal solid wastes. J Environ Sci Health Part A 55: 1339-1348. https://doi.org/10.1080/10934529.2020.1794207 ![]() |
[35] |
Alster CJ, Baas P, Wallenstein MD, et al. (2016) Temperature sensitivity as a microbial trait using parameters from macromolecular rate theory. Front Microbiol 7: 1821. https://doi.org/10.3389/fmicb.2016.01821 ![]() |
[36] |
Revankar AG, Bagewadi ZK, Bochageri NP, et al. (2023) Response surface methodology based optimization of keratinase from Bacillus velezensis strain ZBE1 and nanoparticle synthesis, biological and molecular characterization. Saudi J Biol Sci 30: 103787. https://doi.org/10.1016/j.sjbs.2023.103787 ![]() |
[37] |
Jin Q, Kirk MF (2018) pH as a primary control in environmental microbiology: 1. thermodynamic perspective. Front Environ Sci 6: 21. https://doi.org/10.3389/fenvs.2018.00021 ![]() |
[38] |
Jiang J, Sun YF, Tang X, et al. (2018) Alkaline pH shock enhanced production of validamycin a in fermentation of Streptomyces hygroscopicus. Bioresour Technol 249: 234-240. https://doi.org/10.1016/j.biortech.2017.10.012 ![]() |
[39] |
Kim JM, Lim WJ, Suh HJ (2001) Feather-degrading bacillus species from poultry waste. Process Biochem 37: 287-291. https://doi.org/10.1016/S0032-9592(01)00206-0 ![]() |
[40] |
Nnolim NE, Okoh AI, Nwodo UU (2020b) Bacillus sp. FPF-1 produced keratinase with high potential for chicken feather degradation. Molecules 25: 1505. https://doi.org/10.3390/molecules25071505 ![]() |
[41] |
Abusham RA, Rahman RNZR, Salleh AB, et al. (2009) Optimization of physical factors affecting the production of thermo-stable organic solvent-tolerant protease from a newly isolated halo tolerant Bacillus subtilis strain rand. Microb Cell Factories 8: 20. https://doi.org/10.1186/1475-2859-8-20 ![]() |
[42] |
Cai CG, Lou BG, Zheng XD (2008) Keratinase production and keratin degradation by a mutant strain of Bacillus subtilis. J Zhejiang Univ Sci B 9: 60-67. https://doi.org/10.1631/jzus.B061620 ![]() |
[43] |
Parashar D, Bhatia D, Malik DK (2017) Optimization of keratinase production by Bacillus olironius isolated from poultry farm soil. J Pure Appl Microbiol 11: 1129-1134. https://doi.org/10.22207/JPAM.11.2.58 ![]() |
[44] |
Barman NC, Zohora FT, Das KC, et al. (2017) Production, partial optimization and characterization of keratinase enzyme by Arthrobacter sp. NFH5 isolated from soil samples. AMB Express 7: 181. https://doi.org/10.1186/s13568-017-0462-6 ![]() |
[45] | Zhang YZ, Zhang WX, Chen XL (2020) Mechanisms for induction of microbial extracellular proteases in response to exterior proteins. Appl Environ Microbiol 86: e01036-20. https://doi.org/10.1128/AEM.01036-20 |
[46] |
Shen N, Yang M, Xie C, et al. (2022) Isolation and identification of a feather degrading Bacillus tropicus strain gxun-17 from marine environment and its enzyme characteristics. BMC Biotechnol 22: 11. https://doi.org/10.1186/s12896-022-00742-w ![]() |
[47] |
Wang L, Qian Y, Cao Y, et al. (2017) Production and characterization of keratinolytic proteases by a chicken feather-degrading thermophilic strain, Thermoactinomyces sp. YT06. J Microbiol Biotechnol 27: 2190-2198. https://doi.org/10.4014/jmb.1705.05082 ![]() |
[48] | Wu XQ, Chen L, Cao ZJ, et al. (2012) Feather degradation and keratinase production by Stenotrophomonas maltophilia DHHJ. Adv Mat Res 550: 1400-1403. https://doi.org/10.4028/www.scientific.net/AMR.550-553.1400 |
[49] |
Jaishankar J, Srivastava P (2017) Molecular basis of stationary phase survival and applications. Front Microbiol 8: 2000. https://doi.org/10.3389/fmicb.2017.02000 ![]() |
[50] |
Pletnev P, Osterman I, Sergiev P, et al. (2015) Survival guide: Escherichia coli in the stationary phase. Acta Nature 7: 22-33. https://doi.org/10.32607/20758251-2015-7-4-22-33 ![]() |
[51] |
Yamamura S, Morita Y, Hasan Q, et al. (2002) Keratin degradation: a cooperative action of two enzymes from Stenotrophomonas sp. Biochem Biophys Res Commun 294: 1138-1143. https://doi.org/10.1016/S0006-291X(02)00580-6 ![]() |
[52] |
Jeong JH, Park KH, Oh DJ, et al. (2010) Keratinolytic enzyme-mediated biodegradation of recalcitrant feather by a newly isolated Xanthomonas sp. P5. Polym Degrad Stab 95: 1969-1977. https://doi.org/10.1016/j.polymdegradstab.2010.07.020 ![]() |
[53] |
Peng S, Li H, Zhang S, et al. (2023) Isolation of a novel feather-degrading Ectobacillus sp. JY-23 strain and characterization of a new keratinase in the M4 metalloprotease family. Microbiol Res 274: 127439. https://doi.org/10.1016/j.micres.2023.127439 ![]() |
[54] |
Sandström V, Chrysafi A, Lamminen M, et al. (2022) Food system by-products upcycled in livestock and aquaculture feeds can increase global food supply. Nat Food 3: 729-740. https://doi.org/10.1038/s43016-022-00589-6 ![]() |
[55] |
Callegaro K, Brandelli A, Daroit DJ (2019) Beyond plucking: feathers bioprocessing into valuable protein hydrolysates. Waste Manag 95: 399-415. https://doi.org/10.1016/j.wasman.2019.06.040 ![]() |
[56] |
Zhang J, Su C, Kong XL, et al. (2022) Directed evolution driving the generation of an efficient keratinase variant to facilitate the feather degradation. Bioresour Bioprocess 9: 38. https://doi.org/10.1186/s40643-022-00524-4 ![]() |
[57] |
Safari H, Mohit A, Mohiti-Asli M (2024) Feather meal processing methods impact the production parameters, blood biochemical indices, gut function, and hepatic enzyme activity in broilers. J Anim Sci 102: skae068. https://doi.org/10.1093/jas/skae068 ![]() |
[58] | Fitriyanto NA, Ramadhanti Y, Rusyadi I, et al. (2022) Production of poultry feather hydrolysate using HCl and NaOH as a growth medium substrate for indigenous strains. Earth Environ Sci 951: 012064. https://doi.org/10.1088/1755-1315/951/1/012064 |
[59] |
Tamreihao K, Devi LJ, Khunjamayum R, et al. (2017) Biofertilizing potential of feather hydrolysate produced by indigenous keratinolytic Amycolatopsis sp. MBRL 40 for rice cultivation under field conditions. Biocatal Agri Biotechnol 10: 317-320. https://doi.org/10.1016/j.bcab.2017.04.010 ![]() |
[60] |
El Salamony DH, Hassouna MSE, Zaghloul TI, et al. (2024) Bioenergy production from chicken feather waste by anaerobic digestion and bioelectrochemical systems. Microb Cell Fact 23: 102. https://doi.org/10.1186/s12934-024-02374-5 ![]() |
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